Reason Engine
Our deliberation core. It plans, self-critiques, and explains — turning raw model output into decisions you can defend. Tunable confidence thresholds decide when to act, ask, or escalate.
Everything you need to build, connect, ship, and watch reasoning agents — from a visual studio to a production-grade observability layer.
Our deliberation core. It plans, self-critiques, and explains — turning raw model output into decisions you can defend. Tunable confidence thresholds decide when to act, ask, or escalate.
120+ native connectors plus a typed API gateway. Agents read from and write back to your CRM, warehouse, ticketing, and internal services — securely, with full audit logging.
A visual canvas to design agent behavior, define tools, set guardrails, and test against real scenarios — no PhD required.
Python and TypeScript SDKs plus a CLI for teams who'd rather build in code. Versioned, testable, CI-friendly.
Trace every reasoning step, every tool call, every decision. Replay runs, diff versions, and catch drift before users do.
Policy engine for PII handling, action limits, and approval routing. Compliance teams get the controls they need.
Continuous evaluation against your own benchmarks, so quality is measured — not assumed — on every release.
Run distilled reasoning close to your data for sub-second decisions, with seamless fallback to larger models.
Define a tool, wire a connector, set a guardrail, and ship. The same primitives scale from a weekend prototype to a governed, audited deployment serving the whole company.
Get API access# spark up a reasoning agent from sparkinect import Agent, tools agent = Agent( engine="reason-core", tools=[tools.crm, tools.warehouse], on_high_stakes="ask_human", ) decision = agent.run( "Should we extend net-60 terms" " to Acme on this renewal?" ) # → decision.action, decision.why
Spin up a reasoning agent against your own data and tools. We'll help you scope the first decision worth automating.
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