Context
Every interaction your AI agents handle becomes shared organizational intelligence - eliminating data silos and turning every conversation into context the entire enterprise can act on.
Agent interaction data extracted and classified
Agent interaction data extracted and classified
Extract real-time data from every interaction
Every agent interaction generates transcripts, recordings, metadata, timestamps, and signals about your customers and operations - historically unrecorded, now captured automatically.
Transform and ingest data at scale
Agents automatically parse extracted data into fields like outcomes, intents, contact reasons, sentiments, triggers, and write directly to Context. Every interaction feeds downstream workflows, interfaces, and external systems so data is comparable without any manual effort.
Raw data turned into intelligence at scale
Raw data turned into intelligence at scale
Entity mapping
Every data point captured is automatically mapped to the entity it belongs to - contacts, accounts, vendors, shipments - building a structured understanding of your operation over time so agents reason across your entire operation.
A contact profile that builds with every interaction
Every contact builds a persistent record across interactions - memory snippets, structured extracted attributes, and behavioral tags derived from patterns across sessions. Agents use this record to open every conversation with genuine awareness of customer history.
Unified identity across channels
Phone numbers unify voice and SMS. Email unifies chat and email. Identifiers like tracking numbers or account IDs serve as pivot keys where neither is available, ensuring every touchpoint connects to the same contact record, regardless of channel.
Native integrations to applications your business already runs on
Your enterprise systems, integrated
Context connects to structured data in Salesforce, MongoDB, CRMs, ticketing systems, and 200+ other integrations so every agent operates on live, accurate data without building a separate pipeline.
Two-way data flow via REST API
Context exposes a public REST API and managed REST gateway, so external systems can push data in, pull data out, or query on demand so your AI workforce and data stack always stay in sync.
Knowledge bases
Unstructured data such as documents, policy references, SOPs, and domain knowledge live in knowledge bases and are ingested and retrieved based on the context of live agent interaction.
Intelligence built into deployment from day one
All agents within a deployment share the same Context layer, reusing integrations, contact memory, and data schemas. The more agents you run, the richer it gets, surfacing operational intelligence that never existed before in your enterprise. Insights captured in support fuels sales opportunities. Details from onboarding inform renewals. Shared context across your AI workforce turns every interaction into a competitive advantage. Forward Deployed Engineers (FDEs) can accelerate deployments by helping integrate your enterprise systems, configure knowledge bases, and set up and configure Context from day one so your AI workforce operates on live, accurate data from the moment you go live.
Use intelligence to build and use Context
Use intelligence to build and use Context
Connect your systems
Describe the systems you want to integrate and the intelligence layer sets up polling tables, configures sync schedules, and wires up credentials so your AI workforce operates on live data from day one.
Define schemas and knowledge bases from chat
Tell the copilot what data your agents need to capture and it defines the schema, sets up extraction rules, and configures knowledge bases, ready for agents to read from and write to immediately.
Evolve context as your operation grows
As your AI workforce expands, the intelligence layer helps you add new data sources, update entity mappings, and refine what gets captured without rebuilding from scratch.
