Context
Every system you already run and every interaction your agents handle, mapped into a single data layer that agents read from and write to, helping compound learning with every conversation.
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External Systems
The systems and datalake your business already runs on, can be made available to agents as live, accurate records.
- 200+ native integrationsConnect Salesforce, MongoDB, CRMs, ticketing systems and 200+ more so agents operate on live records.
- Two-way REST APIA public API and managed gateway let external systems push data in, pull it out, or query on demand.
- Knowledge BasesDocuments, policy references and SOPs are retrieved based on what's happening in the live interaction.
Edge
Everything your agents produce becomes structured data: what was said, what was decided, and what happened next.
- Automatic captureEvery interaction becomes structured data as it runs: transcripts and recordings, as well as the outcome, intent, contact reason and sentiment extracted from them.
- Custom variablesBeyond outcome, intent and sentiment, capture any variable that matters: a quoted price, a document reference, a compliance acknowledgment.
- One brain every agent pulls fromWhat a support workflow learns, a sales agent already knows. With cross-functional knowledge sharing, every run makes every other agent better.
Memory
A persistent record of every contact and entity, so agents open each conversation already knowing the history.
- Entity MappingEvery data point maps to the contact, account, vendor or shipment it belongs to, automatically.
- ContactsMemory snippets, extracted attributes, and behavioral tags accumulate across sessions into one persistent record.
- Relevance over volumeAn agent opens with only the details specific and relevant to the upcoming conversation, instead of everything on file.
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14 attributes on file
Every agent operates like a veteran
Every workflow run writes back to Context, so the record grows as a by-product of the work. The more functions agents cover, the more it spans tables that never talked to each other. What accumulates is enterprise-wide operational context that enables every agent to handle customer interactions like your most tenured employee.
Enterprise SuperintelligenceFAQs
Context is HappyRobot's agent-native data layer, the connective tissue binding workflows, enterprise systems, and operational intelligence together. Agents query Context mid-conversation and write outcomes to it after interactions end, making data part of live execution rather than a downstream report.
Context is not a shared reporting table bolted onto the platform. Every organization gets its own fully isolated instance, and agents read from and write to it as a natural part of workflow execution, combining enterprise system data with agentic interaction data in one place.
Context stores three kinds of data in one model: data ingested from systems of record (via polling tables synced with external APIs), data produced by workflows (outcomes, extracted variables, escalation records), and custom operational data with schemas teams define themselves.
Memory is Context's cross-session memory layer. It builds a persistent record for every contact across three dimensions: semantically searchable memory snippets from past interactions, structured extracted attributes (preferences, account details), and behavior-based tags, so agents never treat returning contacts as strangers.
Context exposes a public RESTful API and a managed REST gateway, making it a two-way integration point: external systems like data lakes, BI tools, and analytics platforms can push data in or pull data out on demand, without a separate data pipeline for the AI workforce.
