Tresic is the intelligence layer for communications platforms. Every conversation your network already carries becomes structured, standards-based intelligence, delivered inside your own product, under your own brand, on infrastructure you choose.
The vCon is an open IETF-track standard that packages a conversation - recording, transcript, parties, metadata - into a single portable JSON object. Tresic carries its intelligence as an extension on that object. A system that does not understand the extension still reads the conversation, so the intelligence travels with the record instead of living in a vendor's database.
Datetime, duration, direction, and every party on the conversation.
The customer and the employees, resolved against that business's own customer records and staff roster.
Industry-specific topic and sub-topic, call disposition, and conversation type.
A factual summary of who, why, what and outcome, with sentiment and the direction it moved during the conversation.
What has to happen next, with an owner, a priority, and a suggested date.
Discrete detections, each carrying the evidence that produced it: churn, escalation, complaint, buy signal, expansion, product request.
A resolution state you can build a worklist on, not a score you can only display.
Competitor and partner mentions, matched deterministically against each tenant's own tracked lists.
Tresic reads what your platform already produces and hands intelligence back. Nothing your customers experience about placing or answering a conversation changes, which is what makes it deployable across a live base rather than a migration programme.
Recording or transcript plus the metadata you already generate, from the infrastructure layer you already control.
One enriched vCon per conversation, resolved against that customer's own employee roster and customer records.
Your branded portal, components embedded in screens your customers already use, a webhook into their systems, or your own front end over the API.
Deployable surfaces sitting on the same enriched object, so nothing has to be built to make the layer useful. Together they cover the whole arc: the record of each conversation, the alert when one matters, the numbers across all of them, and the worklists a business runs its day on.
Every conversation leaves a factual record: what it was about, what was said, what happens next, and a follow-up with an owner and a date. Searchable across everything that came before.
Rapid alerts on the conversations that need someone now, with the conversation attached so a person can judge it in seconds.
The numbers over the whole enriched corpus - trending topics, anomalies, cross-location comparison - and Ask Tresic, which answers a question asked in plain language with the conversations that prove it.
Where the business is actually run. Role-scoped worklists driven by the signal set: what needs attention today, account health, sales and expansion, voice of the customer, and a watch board per account group.
The APIs, webhooks, and SDKs behind all of it, available to you and to anyone building on your platform.
Where each business configures what is tracked and how its data is handled. Self-service, and the reason the intelligence knows a business instead of guessing at it.
Every surface can carry your brand on your domain, be embedded into screens your customers already use, or be skipped entirely in favor of your own front end over the API.
Everything the platform produces is addressable, in both directions. Consume the intelligence, keep reference data in step with the systems your customers already run, and push insight wherever their teams work.
A webhook fires on every processed conversation with the full enriched object, plus separate events for the alert triggers each business configures. Signed, retried, idempotent.
Read any conversation back, or query across the whole enriched corpus, through a versioned REST surface.
Keep customers, employees, key accounts, and tracked competitors in step with each business's system of record, so the intelligence stays attributed to real people and real accounts.
Automated agents that route on intent, urgency, and risk. Assistants that open a conversation already knowing the account's history. Conversation intelligence flowing into a warehouse alongside everything else a business measures. Workflow that starts itself because the signal arrived with its evidence attached. Portals a partner builds entirely themselves.
The signal architecture is built so new detections arrive on the same contract you already consume. What you integrate against today keeps working as the set deepens, and every industry brought to production adds classification your customers inherit without asking for it.
Conversation intelligence is becoming a standard part of every communications platform. What comes after analytics is the operational layer: once a platform knows what happened in every conversation, who it involved, and what has to happen next, it can become the system a business runs its operations on. Operations Hub is the first step onto that ground, and it is where most of what we build next will land.
The arc runs from capturing what happened, to flagging what matters, to assigning and closing the work itself. Each step is a larger surface for a platform to own, and each one sits on the same enriched object you already integrate against.
The work that makes a signal behave correctly in one industry does not have to be done again. Production industries carry their topic taxonomies, disambiguation rules, and signal criteria with them, so a platform turning on a new vertical starts from that work rather than from scratch.
Intelligence carried on an open conversation standard moves through an ecosystem instead of pooling inside one vendor. Tresic contributes to the vCon work on the IETF standards track and to the CPaaS Acceleration Alliance AI and Data working group, where the shape of this category is being decided.
Your customers' conversations belong to your customers. Every tenant is isolated at the API layer from the access token, never from a client-supplied identifier, with row-level separation beneath it and physical separation where a regulated tenant requires it. Partners holding raw transcripts get their own storage with independent access control.
One customer's conversations are not pooled into another customer's intelligence. Card data is redacted before anything is written to durable storage, records are classified at ingestion and retained by class, and every ingest and access event is logged to an append-only trail. Any corpus used for validation is irreversibly anonymized first.
The most direct way to evaluate a layer like this is to run it against your own traffic and read what comes back. That is the same conversation whether you are assessing an integration, an API, or the platform itself.