Context Ontology for Telecom & Media: Give AI the Links Between Network, Customer, Contract and Rights

AI for Telecom
Network-to-Customer Ontology
Content Rights Management
Context Ontology Accelerator
AWS Context

Context ontology for telecom and media gives AI agents the connections your systems keep apart: which services and customers depend on a network element, which contract and SLA cover them, and which titles may play in which territory, on which tier, on which date. Care, network and content agents read it before they answer, so an outage reply names the right customers and a rights check agrees with the licence. Mactores builds it with your network, care and rights leads inside your AWS account, starting on the Context Ontology Accelerator and moving to AWS Context once AWS releases it, with fee and ship date fixed in the SOW before work begins.

At 02:10 a fault alarm fires on a cell site that serves a business park. The network operations agent sees a resource ID. The care agent sees subscribers calling about dropped calls. Neither can tell that three enterprise customers with four-hour restoration SLAs sit behind that site, that one of them is halfway through a renewal, or that the retention engine is about to send discounts to people whose only complaint is the outage. Fault management, inventory, billing and the contract repository each hold a piece. The map that joins them is what's missing, and no agent can improvise it in the middle of the night.

Bring one alarm or one title your agents answer badly

Show us the question, the systems it touches and what the agent said.

In one working session we find the missing links, outline a first release and name a ship date you can plan around.

Book a scoping call

12 weeks: until Safaricom's intent-based care agents were delivering value
4: service domains, from billing to troubleshooting, shared by Safaricom's cooperating agents
10M+: subscribers scored by a churn and intervention platform Mactores built
94%: of Mactores programs delivered on or before the contracted date
2008: the year Mactores began building on AWS

Competency: AWS Data and Analytics Consulting Competency
Specialization: AWS Agentic AI Specialization
Partner tier: AWS Premier Tier Services Partner

Top Mactores Clients

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Customers include Safaricom, Synaptics, Flipboard, Poshmark, Seagate, HP, Adani, DocuSign, KlearTrust, Tilia, Sterne Kessler and Total Expert.

Why Can't a Telco Agent Connect a Network Alarm to the Customer Contract Behind It?

Because no single system holds the chain. Fault management knows the network element, inventory knows which services ride on it, billing knows the subscriber and the contract repository holds the SLA, each under its own identifiers. An agent sees one link at a time. A context ontology records the whole chain, so the agent can follow it in one query.

Media platforms hit the same gap with different nouns. A title is an asset in media asset management, a product in the storefront, a line in a licence agreement and a row in an avails spreadsheet. Whether it may stream in Brazil on the ad-supported tier next month depends on all four, plus holdbacks and blackout terms buried in contract wording. Document retrieval can find the contract. It cannot work out the window.

Operators and media companies are putting agents in front of these questions anyway:

79%

of communications service providers expected to have AI agents running in production by Q4 2026, against 31% in Q4 2025, in a Coleman Parkes survey for Amdocs published in May 2026.
81%

of operators in TM Forum research aim to reach Level 4 autonomous networks or higher by 2030, though only about one in five expect to get there by 2027.
17%

of media and entertainment firms say agentic AI is fully built into their workflows, close to twice the 9% across all industries in the same Grant Thornton study.

Behind those numbers, the same failures repeat across operators and platforms:

Symptom	Root cause	What the ontology settles
Care agents blame the handset during a known outage	Incident data never reaches the care channel	Incidents linked to the cells, services and subscribers they affect
Enterprise SLA credits are missed, or paid twice	Contracts sit apart from the circuits and sites they cover	Each SLA tied to the services, sites and restoration targets it promises
A retention discount reaches a customer mid-outage	Churn models and offer engines can't see network events	Offers checked against open incidents and recent service quality
A title plays where its window has closed	Rights live in contracts and avails feeds the catalog can't read	Titles, territories, windows and holdbacks modeled as checkable rules
Finance, product and partners report different subscriber counts	Subscriber, household, account and profile are counted differently	One definition of each, owned by the team that reports it
Nobody can explain why an agent answered as it did	No record of sources, definitions or the policy applied	A trace per answer, kept for regulators and rights holders

Where the industry is heading raises the cost of that gap. Level 4 autonomy means the network acts on faults without waiting for a person, which only works when automation knows what a fault means for customers and contracts rather than for a single node. On the media side, Grant Thornton's 2026 AI impact survey of the sector shows adoption running ahead of most industries, and every automated decision about where a title plays is one a rights holder can audit later.

Outage replies blaming the customer's phone?

Send one incident and the answers your care agent gave.

We'll show which links it was missing.

Request an incident review

What Does a Network-to-Customer and Rights Ontology Contain?

It contains the entities your agents need and the links between them: customers, accounts and households; offers, plans and contracts; services, lines and devices; network elements, incidents and work orders; titles, territories, windows and rights. It also holds the rules, such as SLA targets, consent and availability, written as checks agents run before answering.

Scoping starts from questions, not from a data model. Your network operations, care and content rights leads each name the questions their agents should own, every one assigned an owner and an expected result. Ten to 20 of those set the boundary of the first release and the test it must pass before anyone relies on it.

Entity	What it captures	Source systems today
Customer, account and household	The paying party, its billing accounts, the people in a household and the subscribers on each line	CRM, BSS billing, customer identity platform
Offer, plan and bundle	What each price plan and bundle includes, with eligibility rules and effective dates	Product catalog, BSS, pricing tools
Service, line and device	Subscriptions, SIMs and eSIMs, numbers, broadband lines and the devices on them	Order management, provisioning, device management
Network element and site	Cells, sites, routers, circuits and routes, with the services each one carries	OSS inventory, network planning, topology tools
Incident and work order	Alarms, tickets, outages and field jobs, linked to the elements and customers affected	Fault management, service assurance, field service systems
Contract and SLA	Enterprise agreements, availability and restoration targets, and credit terms	Contract repository, CRM, enterprise billing
Content asset	Series, seasons, episodes, films, live events and channels, with identifiers and versions	Media asset management, catalog, EIDR records
Rights, territory and window	Who licensed what, where, on which platforms and tiers, from when to when, with holdbacks and blackouts	Rights management system, avails feeds, licence agreements
Viewer, profile and entitlement	Accounts, profiles including kids profiles, entitlements by tier and region, and consent	Subscriber management, consent platform, identity provider
Ad slot and campaign	Inventory, campaigns, audience segments and frequency caps, with content suitability rules	Ad server, campaign tools, IAB taxonomies

Delivered in release one:

An ontology covering the network, customer, contract and rights questions your owners approved, running in your AWS account
One customer and household identity across CRM, billing and subscriber management
The impact chain from network element to service, customer and SLA, refreshed as topology changes
Availability rules for the titles in scope, combining avails feeds and licence terms into checks an agent can run
CPNI, consent and kids-profile policies applied on every query path
A regression set of questions with expected answers that gates each publish, plus runbooks and stewards who can run it

Drafted by agents

Candidate classes and links read from OSS, BSS, CRM and catalog schemas
Matches between inventory IDs and service and billing records, each scored for confidence
Licence terms, territories and windows pulled from contracts and avails feeds for review
Suggested alignments to TM Forum SID and EBUCorePlus where your data fits them
Re-runs of every test question whenever a mapping changes

Decided by your network, care and rights owners with our FDEs

Whether "customer" means the account, the line or the household for each question
Which SLA wins when a contract and a standard plan disagree
What counts as an affected customer during a partial outage
How a holdback or blackout overrides a licence window
Which questions agents may answer without a person in the loop

That split mirrors how the accelerator works, with agents proposing and people deciding. AWS credits its drafting step with cutting ontology authoring from months to days. For a telco, the saved time usually goes to the hardest meeting in the program, where network, care and billing teams agree what an affected customer is.

How Is This Different From a Data Catalog or TM Forum SID?

Most operators already run a data catalog and some alignment with the TM Forum Information Framework, known as SID. Both stay. SID gives operators a shared vocabulary for customers, products, services and resources, but it is published as a UML model rather than in a form agents can reason over, and every operator implements it a little differently. The ontology reuses SID names where they fit and records your local variations as mappings.

Question	Data catalog	Context ontology
What does it describe?	Tables, columns, owners and lineage	Business entities, their relationships and the rules governing each
Who reads it?	Analysts and data stewards	Agents, applications and analysts
Can an agent follow alarm to SLA?	No, it shows where data sits	Yes, the links are modeled and queryable
Does it hold policy?	Sometimes, as tags	Yes, as checks run on every query
Is it tested against answers?	Rarely	Every publish reruns the agreed questions

Choose the questions your agents should own first

Each question becomes part of release one's scope

and its acceptance test.

Draft my release scope

What Can AI Agents in Telecom and Media Answer Once Everything Is Linked?

AI agents in telecom and media can then answer questions that cross teams: which enterprise customers sit behind an alarm and what their SLAs promise, whether a caller's problem is a known outage, whether a title may stream in a territory on a given tier and date, and which ads may run beside children's programming.

Network and care questions usually come first, because a wrong answer there costs money within hours: SLA credits, repeat calls and field crews sent to the wrong site. Rights questions follow on the same model, and gaming and sports teams add theirs once identity and consent are settled.

Question	Who asks	What has to be true
Which enterprise customers with a four-hour restoration SLA are behind this alarm cluster, and when does each clock run out?	Network operations center and enterprise service desk	Elements linked to circuits, services, sites, customers and SLA terms
This caller reports dropped calls: is there an open incident on their serving cells, and should care offer a credit?	Care staff and the AI assistant beside them	Subscriber linked to line, device, serving cells and incidents, with credit rules
Can we stream season two in Brazil from 1 March on the ad-supported tier?	Content operations, scheduling and storefront teams	Title, territory, platform, tier and window linked, with holdbacks applied
Which households received the new bundle offer while an outage affected their area?	Retention and marketing	Offers, households and incidents on one timeline
Which campaigns may run against this channel's children's programming in the UK?	Ad operations	Content ratings, kids flags, campaign categories and territory rules linked
Which players saw the new bundle price, and did their spend change the following week?	Game economy and live ops teams	Players, offers, price tests and purchases linked, with minors' data excluded

Every answer names its sources and the policy that allowed it. The streaming, telemetry and subscriber data behind these questions comes through our data platform practice, giving the ontology inputs that arrive complete and on schedule.

Have a question three teams answer three ways?

Send it with the systems behind it,

and we'll show where the answers part company.

Trace the answers

How Does a Context Ontology Answer “Can We Stream This Title, Here, on This Date”?

It splits the question into three tiers. A governed availability status answers directly when one exists, with no language model involved. If not, a graph query walks title, territory, platform, tier and window, applying holdbacks. Only clauses no feed captures go to an agent reading the licence. The Context Ontology Accelerator serves all three paths today.

The accelerator has been generally available as Apache 2.0 open source since 31 July 2026. According to AWS's launch note, Amazon Neptune holds the graph, Amazon OpenSearch Serverless holds the document index and Amazon Bedrock supplies the models, all in your account, with requests answered over MCP and SPARQL. It is self-managed, comes without AWS Support and includes no telecom or media models, so SID alignment, rights logic and SLA rules are built for you. AWS plans for ontologies built with it to carry into AWS Context, a managed service announced in June 2026 that still has no release date.

How Does One Rights Question Resolve?

Take a scheduler asking whether season two of a drama can stream in Brazil from 1 March on the ad-supported tier.

01 Tier one: a governed status. If availability per title, territory and tier is already computed from the avails feed, the answer comes from that record and no model is called.
02 Tier two: a graph query. If the status isn't precomputed, a SPARQL query over a virtual knowledge graph walks licence, territory, platform and window, reading your rights tables in place, and applies any holdback, such as an exclusive pay TV window that keeps the season off ad-supported tiers until May.
03 Tier three: an agent over documents. Avails feeds often have no field for newer licence types such as free ad-supported channels. When the licence wording decides the answer, the agent reads the clause under the same access rules and cites it.

The alarm question takes the same route. The count of affected subscribers comes from a governed figure, the path from cell site to enterprise customer and SLA comes from the graph, and the credit wording comes from the contract. On every path, Cedar authorization and the accelerator's SQL firewall decide what the caller may see, so CPNI and kids profiles stay out of answers that have no need for them.

What Happens in the Scan, Model and Serve Steps for Telcos and Media Platforms?

01 Scan. Point the accelerator at the systems behind your first questions: OSS inventory and fault management, BSS billing and CRM, the product catalog, the rights management system and avails feeds, the media asset catalog, and documents such as enterprise contracts and licence agreements. Metadata is enriched automatically, and probable matches go to owners for review.
02 Model. Once network, care and rights owners sign off the draft, each concept becomes a W3C OWL class, SLA and availability logic is expressed in SHACL, and R2RML maps every class to the source tables that hold it.
03 Serve. Care, network and content agents reach the ontology over MCP, analysts and partners use SPARQL, and each tool definition lists what its callers may ask.

Which Telecom and Media Standards Does the Ontology Build On?

Both industries have mature vocabularies, though few were published as ontologies. We align to the ones your systems already use:

Standard	Covers	Role in your ontology
TM Forum Information Framework (SID)	Customer, product, service and resource entities for operators, published as a UML model	Source names for telecom classes, with your variations kept as mappings
TM Forum intent ontology	Operational goals expressed as machine-readable intents, in RDF and OWL	Links network intents to the services and customers they protect
EBUCorePlus	Broadcast and media asset metadata, published by the EBU as an OWL ontology	Base classes for content assets, versions and channels
MovieLabs Ontology for Media Creation	Production entities such as scripts, shots and assets, in RDF	Connects production assets to the titles they become
EMA and MovieLabs Avails	Spreadsheet and XML formats for availability windows by territory and format	Imported as windows and terms, then checked against licence clauses
EIDR	Unique identifiers for films, series, episodes and edits	One identity per title across catalog, rights and partners
DDEX	Message standards for music releases, rights and royalty reporting	Music and audio rights for platforms that carry them
IAB Tech Lab Content Taxonomy	Standard categories for describing content to advertisers	Content suitability rules for ad placement
IPTC SportsML and schema.org SportsEvent	Sports events, results and statistics	Matches, competitions and teams for sports rights and data products

Want to watch one rights question resolve?

We'll run a title, a territory and a date through the accelerator

using a sample of your avails.

Run a rights check

How Does Delivery Fit Around Network Change Windows and Live Events?

In five phases, and none closes without a signature: choose the questions, map customers and the network, agree definitions and rules, prove answers and policies, then switch agents over. Releases follow your change management, avoid freeze periods around launches and major live events, and reach production in the same windows your network changes use.

How we work applies to every Mactores program. For operators and media companies it mostly means respecting the calendar. Definition sessions stay clear of network change freezes, ontology changes pass through your change advisory process like any other release, and nothing new reaches care or playout systems in the weeks before a tentpole event.

Phase 01
Choose the questions

What happens

Network operations, care and content rights leads agree 10 to 20 priority questions, give each an owner and an expected result, and note the systems involved; the ship date goes into the SOW

Owner

Shared

Signed exit

SOW and question set countersigned
Phase 02
Map customers, network and catalog

What happens

Agents scan OSS, BSS, CRM and catalog schemas, and matches between inventory, service and billing IDs, and between catalog and rights records, are reviewed with system owners

Owner

Agents and FDEs

Signed exit

Identity and topology map approved
Phase 03
Agree definitions and rules

What happens

Teams settle what an affected customer, an active subscriber and an available title mean; SLA, consent and availability rules become checks; CPNI and children’s data policies are written with privacy and legal

Owner

FDEs and your teams

Signed exit

Owners sign every definition and rule
Phase 04
Test answers and policies

What happens

Agents answer the test questions, replayed incidents and past rights decisions are compared with what really happened, and probes confirm restricted data stays out

Owner

Agents and FDEs

Signed exit

Accuracy and policy results accepted
Phase 05
Switch agents over

What happens

Care, network and content agents move to the ontology one channel at a time inside approved change windows, and runbooks pass to your operations team

Owner

Shared

Signed exit

Acceptance signed by you

Every care, network and content agent must pass this gate:

01 Each question in scope has one owner, one expected answer and a version
02 Every subscriber resolves to one customer, account and household across CRM, billing and subscriber management
03 Links from element to service to customer match inventory for the regions in scope
04 Replayed incidents name the same enterprise customers your service desk confirmed at the time
05 Rights answers match past scheduling decisions for a sample of titles and territories
06 CPNI, consent and kids-profile probes are refused by every tool agents can call
07 Tests for prompt injection and overly broad queries pass
08 Each answer stores its sources, definitions, policy decision and ontology version
09 The accelerator version is fixed, and each upgrade is tried in staging first
10 Load tests at expected outage or live-event volume pass, with cost alerts and rate limits set

At the close of phase one, the SOW locks scope, fee and delivery date together. Delays we cause are ours to absorb. If one originates with you, for example a late OSS data extract or a rights owner missing a review, the extra time is billed at the hourly rate the SOW sets. Our commitment has the complete terms.

Fit phase one around your next change freeze

Phase one ends with your questions signed off

and a ship date that respects your calendar.

Set my phase one dates

How Do You Keep CPNI and Children’s Data Out of an Agent’s Answers?

By policy on every query path, not by instructions in a prompt. CPNI, consent status and kids-profile flags are modeled as attributes, Cedar policies decide which callers and purposes may see them, and the SQL firewall blocks queries that would pull them in bulk. Each answer records what was withheld and why.

CPNI covers what a carrier knows because it provides the service: who a customer calls, when, for how long, from where, and what they subscribe to. FCC rules limit its use beyond the service relationship without the customer’s approval, require safeguards against pretexting and call for an annual compliance certification. A care agent may use call records to troubleshoot a line. A marketing agent should never see them unless the customer has opted in, and CPNI compliance depends on proving that difference for every answer.

Carrier breach rules are also unsettled. The FCC’s December 2023 breach reporting order extended notification duties from CPNI to a wider set of personal data. A Sixth Circuit panel upheld it in August 2025, but the full court agreed in July 2026 to rehear the challenge, and no ruling had been issued by early November 2026. Agents that cannot reach data they don’t need are the safest design whichever way the court decides.

Children’s data carries its own rules. The amended COPPA Rule, with compliance required since 22 April 2026 under the FTC’s final rule, adds biometric identifiers such as voiceprints to personal information, requires separate parental consent before children’s data goes to third parties for purposes such as targeted advertising, and calls for a written security program and a published retention policy. For a streaming service or game with kids profiles, or a set-top box with voice search, every agent touching those profiles needs to know it.

Purpose before access.

Each tool declares its purpose, such as troubleshooting, restoration or marketing, and Cedar policies admit CPNI only to purposes the subscriber’s approvals cover.
Kids profiles fenced off.

Profiles flagged as children’s are excluded from personalization, ad targeting and model training queries unless verified parental consent is on record.
Actions wait for people.

Agents can explain, look up and draft. Credits, plan changes, takedowns and schedule changes need a person to approve them.
A trace for every answer.

Caller, purpose, sources, definitions, policy decisions and ontology version are kept for regulators, auditors and rights holders.

Requirement	What it expects	How the ontology helps
FCC CPNI rules	Customer approval before CPNI is used beyond the service relationship, safeguards against pretexting and an annual certification	CPNI fields tagged, approvals linked to each subscriber and purpose checked on every query
FCC breach reporting order	Breach notice covering CPNI and broader personal data, with its validity now before the full Sixth Circuit	A clear map of which agents can reach which data, so any exposure can be scoped quickly
Amended COPPA Rule	Separate parental consent for third-party disclosure, a written security program and retention policy, and biometric identifiers covered, with compliance due since 22 April 2026	Kids profiles and consent records modeled, with retention dates attached to the data
EU AI Act, Article 50	Starting 2 August 2026, AI systems must disclose themselves to the people using them and generated or manipulated media must carry a label; systems already on the market have until 2 December 2026 to add marking	Disclosure and labeling recorded with each agent interaction and generated asset
UK Online Safety Act children’s codes	Since 25 July 2025, services likely to be used by children must apply Ofcom’s protection measures, including age checks and safer feeds	Content ratings and age signals linked so agents respect them
GDPR and residency	A lawful basis and a stated purpose for processing subscriber and viewer data, kept in approved locations	Purposes attached to classes, deployed in the Regions your regulators require
Rights holder agreements	Content plays only within licensed territories, platforms and windows, with audit rights	Availability checks and decision logs that line up with the licence

What Can You Show a Regulator or Rights Holder?

Question you will be asked	Evidence you can hand over
Did any marketing agent read call records last quarter?	Policy decisions and access logs filtered by purpose
Which customers did your outage notice reach, and why those?	The impact chain for that incident and the ontology version in force
Why did this title play in Mexico on that date?	The availability decision, the avails record and the licence clause it relied on
How do you keep children’s profiles out of ad targeting?	The policy, the consent records it checks and the probe results
Who signed off the change to the SLA credit rule?	The approval record, who signed it and the tests it passed

Have an audit or rights renewal coming up?

Send the hardest questions you expect,

and we’ll show the evidence an ontology would give you for each.

Map my evidence

Which Telco, Media, Gaming and Sports Teams Use Ontology-Grounded Agents?

Teams where one wrong answer costs money or a licence. Operators start with network-to-customer questions for care and enterprise service. Streaming and broadcast teams start with rights and availability. Gaming studios start with player identity, offers and age signals. Sports leagues and rights holders start with territories, sponsors and match data. Each builds on shared identity.

Telecom operators

Mobile, fixed and cable operators start with the chain from network element to service, customer and SLA. Care agents check open incidents before troubleshooting a line, enterprise desks see which contracts an outage touches, and retention offers wait until service is restored. This is AI for telecom at its most practical: fewer repeat calls, fewer missed credits and field crews sent to the right site. The same model later supports autonomous networks, because closed-loop automation has to know which customers a change will affect. Agentic AI in telecom moves past the pilot stage once care, network and billing agents share this context.

Telco work at Mactores

Streaming and broadcast media

Content rights management leads. Titles, seasons, versions, territories, platforms, tiers and windows are modeled once, avails feeds and licence terms are reconciled into checks, and scheduling, storefront and recommendation agents ask before anything is promoted. Viewer profiles, household entitlements and consent come next, so personalization never touches kids profiles it shouldn't. AI in media and entertainment tends to stall at exactly this point, because a recommendation that surfaces an unlicensed title is a contract breach, not a poor suggestion.

Media and entertainment at Mactores

Gaming studios and publishers

Player identity, accounts across platforms, offers, purchases and age signals form the first model. Live ops and economy teams ask how a price test or bundle changed spend, support agents answer from a player's real purchase history, and minors' data stays out of targeting by policy. For AI in the gaming industry, the hard part is rarely the model. It is knowing which player is which across console, PC and mobile, and which rules apply to each, before telemetry reaches an agent.

Gaming work at Mactores

Sports leagues and rights holders

Leagues, clubs and broadcasters start with competitions, matches, teams, sponsors, territories and media rights. Agents can then say which partner may show a match where, which sponsor categories are exclusive in a market and how a fixture change affects broadcast commitments. Match and player data follow IPTC SportsML or schema.org conventions, so feeds from different providers line up. Fan data comes later, under the same consent rules that protect subscribers and viewers, with children's accounts handled separately.

Sports and entertainment at Mactores

Groups that own both networks and content, such as operators with their own TV service, run the telecom and media patterns on one shared customer identity.

How Is a Telco or Media Ontology Project Priced, and What Does Running It at Peak Cost?

Expect 8 to 12 weeks for a first release of 10 to 20 questions. Price follows the number of questions, source systems and regions, how far inventory and billing records disagree, and how many titles and territories the rights logic covers. Run cost depends mainly on peak traffic, which governed answers keep cheap.

Pricing note. We don’t publish a rate card. Effort tracks the shape of your estate: how many inventory, billing and rights systems disagree, how many regions and brands are in scope, and how much traffic agents will send at peak. The accelerator carries no licence fee. Use the factors below to read a quote; the number that binds is the one in your SOW.

Cost factor	Why it matters
Questions in scope	Each brings its own entities, links, rules and tests
Source systems and regions	Every OSS, BSS, rights system or regional stack adds mappings
Inventory and identity quality	Element, service and customer IDs that disagree need owner review
Rights complexity	More territories, tiers, windows and holdbacks mean more rules to test
Privacy scope	CPNI, consent and children's data add policies and probes
Peak volume	Outage storms and live events set capacity, rate limits and load tests
Platform	The accelerator is self-managed, so someone must own upgrades and on-call: your team or ours

Run cost. AWS bills you for the graph store, document search and model calls. The expensive moments are predictable: an outage sends thousands of customers to care at once, and a live final sends millions to the storefront. The questions that spike at those moments, such as whether an area has a known outage or whether a match is available in a region, resolve from governed answers with no model call, so cost grows with lookups rather than tokens. Per-channel rate limits, capacity raised ahead of scheduled events and development stacks that shut down overnight hold spend steady.

Planning for your next big outage or live event?

Share your questions, source systems and peak volumes,

and we’ll return a fixed fee with a ship date.

Price my first release

Which Telecom and Media AI Terms Should Your Team Know?

Context ontology: A machine-readable model of your network, customers, contracts and content. Agents check it before answering to learn what exists, how things connect, what each term is agreed to mean and the rules in force.
Enterprise knowledge graph: Data about real entities and their links, stored as a graph. An ontology defines the classes, meanings and rules, and the graph holds the instances.
OSS/BSS: Operations support systems run the network side, such as inventory, fault and provisioning. Business support systems run the customer side, such as catalog, ordering, billing and CRM.
TM Forum SID: The TM Forum Information Framework, a shared model of customer, product, service and resource entities that many operators build on.
Service impact analysis: Working out which services, customers and SLAs a network fault or planned change will affect.
SLA credit: Money or service owed to a customer when an availability or restoration target in its contract is missed.
CPNI: Customer proprietary network information: what a carrier knows about a customer's use of its service, such as calls, location and subscriptions, protected by FCC rules.
Content rights management: Tracking which content may be distributed where, on which platforms and tiers, during which dates and on what terms.
Avails: Availability records telling platforms and partners when and where a title may be offered, often exchanged in the EMA format.
Licence window: The start and end dates during which a title may be offered in a territory on a given platform or tier.
Holdback: A clause that keeps a title off certain platforms or tiers for a period, usually to protect an exclusive window elsewhere.
Autonomous networks: Networks that detect, decide and act on operational events with little or no human involvement, graded by TM Forum from Level 0 to Level 5.
Model Context Protocol (MCP): The protocol agents use to discover and call tools. Care, network and content agents reach the ontology through it.
FDE: The Mactores specialist embedded with your network, care and content teams for the whole program, who runs definition sessions and owns the outcome.

How Can Mactores Help You Out?

Choose the entry point that matches where you are; each has its price and ship date agreed before work starts. Agents live but trusted by nobody? We review their answers first. Questions known but answers inconsistent? A first-release context ontology fixes that. One chain causing most disputes? We start with that chain and extend from there.

Since 2008, Mactores has built on AWS for businesses where downtime is public: care centers during outages, streaming platforms during finals, games during launches. The practice that built data infrastructure for millions of concurrent live-event streams brings the same habits to ontology work, with definitions shipped like code, policies tested like security controls and releases timed around your event calendar.

Starting point	Engagement	Result
Care or network agents are live, but staff override their answers	Agent answer review	Each wrong answer traced to the context it lacked, in priority order, with a first-release scope and date
Each system gives a different answer to questions you already know	First-release context ontology	Care, network and content agents answering from one model your stewards maintain
One chain causes most of the pain, such as alarm to SLA or title to window	Single-chain release	That chain modeled, tested and live first, ready to extend

The method is shared across every vertical we serve, and our context ontology services page lays it out, including how we choose between the accelerator and other platforms. Telcos and media companies gain the most from going wider once the first chain works. The customer identity built for care becomes the base for retention and marketing, the topology links built for outage answers feed autonomous operations, and the rights model built for scheduling serves recommendations, partners and ad sales without being rebuilt each time.

If the agents themselves still need building, for care, network operations or content teams, our AI agent development services can deliver them on this ontology, under one contract. You own all of it, in open W3C formats, held in your AWS account, and your stewards learn to extend it. Operators that start with one region or brand typically bring in a second within three months, reusing the identity and policies already in place, which makes each release cheaper than the one before.

Operators' security and procurement teams will ask for credentials, and ours are listed on our AWS partner page: status as an AWS Premier Tier Services Partner, plus the Agentic AI Specialization alongside the Data and Analytics Consulting Competency, both awarded by AWS.

Bring the chain that breaks most often

In the first session we'll show where the links fail

and what a first release would fix, and when.

Book a session with an FDE

What Do Telco and Media Leaders Ask Before They Start?

What is context ontology for telecom?

It is a model of your network, customers, products and contracts, plus your content and rights if you run media services, which AI agents read before they answer. It records how a network element connects to services, customers and SLAs, and how a title connects to territories and windows, so agents follow real links instead of guessing.

Is an ontology the same as an enterprise knowledge graph?

Not quite. The ontology is the schema: classes, meanings, relationships and rules. The knowledge graph is the data shaped by it, such as your actual cell sites, customers and titles. Agents need both, and the accelerator builds both, often reading graph data from your existing tables without copying it.

Is AWS Context available yet?

No. It was announced in June 2026, and as of mid-November 2026 AWS has given no preview or launch date. AWS designed the Context Ontology Accelerator so its ontologies can move there, and the slowest work, agreeing definitions across network, care, billing and rights teams, carries over unchanged.

Does this replace our OSS/BSS or our TM Forum SID alignment?

No. Your OSS and BSS remain the systems of record, and the ontology reads from them. Where your data already follows SID, the ontology reuses its names; where it departs, the differences are recorded as mappings, so agents see one model while your systems keep working as they do.

Do we need clean data before we start?

No. Mismatched IDs between inventory, service and billing records are normal, and the scan phase flags them with a confidence score. Owners resolve the matches that matter for the first questions, and the release gate checks that the chain holds for the regions in scope before agents depend on it.

Can care agents use it during an outage?

Yes, and that is usually the first use. When an incident opens, the impact chain shows which subscribers and enterprise customers are affected, so care agents can acknowledge the outage, give an honest restoration estimate and hold retention offers until service is back.

How do you keep CPNI away from marketing agents?

Each tool declares a purpose, and Cedar policies admit CPNI only to purposes the subscriber's approvals cover. Marketing tools are refused call records unless the subscriber opted in, the SQL firewall blocks bulk extraction, and every refusal is logged with the policy that caused it.

How are children's profiles protected?

Profiles flagged as children's are fenced off by policy: no personalization, ad targeting or disclosure to third parties without verified parental consent, in line with the amended COPPA Rule. Probes test those fences before every release, and a failure blocks it.

What if our avails feeds miss licence terms?

Avails feeds become structured windows in the ontology. Where a feed has no field for a term, such as a newer ad-supported licence type or an unusual holdback, the agent reads the licence clause under the same policies and cites it, and owners can turn frequent clauses into structured rules.

Will it help with autonomous networks?

It supplies something closed-loop automation lacks: knowledge of which services, customers and SLAs a network change affects. Most operators begin with care and service assurance questions, then extend the same impact chain to intent-based and automated operations once it has proved accurate.

Can it cope with peak load from outages and live events?

Yes, when designed for it. The common peak questions resolve from governed answers without a model call, capacity is raised ahead of scheduled events and rate limits protect each channel. Load tests at expected peak volumes are part of the release gate.

How soon can agents use it?

Expect a first release 8 to 12 weeks from the start of phase one, covering 10 to 20 questions for one region, brand or catalog. More regions, systems or rights complexity extend that. Phase one ends with the ship date written into the SOW.

Who owns what you build?

You do. Every artifact, from the ontology and its mappings to the policies, tests and runbooks, lives in your AWS account and your repositories in W3C formats. The SOW fixes ownership and exit terms up front, and your stewards learn to run it without us.

Something we didn't cover?

Email it, with the network, product or title in question,

and an FDE replies.

Email lets-talk@mactores.com

Which Alarm, Title or Metric Do Your Agents Get Wrong?

Send it over. We'll show which links are absent and put a date on fixing them.

01
Meet an FDE for one session covering the question, the systems behind it and your agents' answers.
02
Within a week, get our assessment, a scoped first release and a ship date we're prepared to sign.
03
Sign the fixed-fee SOW to start phase one.

Fix my agents' answers lets-talk@mactores.com

Each engagement comes with a 30-day satisfaction guarantee. Raise a production defect within 90 days of acceptance and we fix it free.