Autonomous agents,
production-grade.
Long-horizon agents with durable memory, typed tool use, and observable traces. Built to run as services — not as scripts someone kicks off from a notebook and watches over.
Everything a production agent needs.
Memory that persists across sessions. Tools that validate their own inputs. Traces you can ship to your existing observability stack. All of it, out of the box.
Durable memory
Vector and relational memory scoped per agent and per session. State survives restarts, rollbacks and version upgrades.
Typed tool use
Schema-validated tools with automatic retries on malformed calls. Agents fail gracefully instead of hallucinating past errors.
Structured output
Enforce JSON schemas on any LLM response. Use constrained decoding for structured extraction without prompt hacks.
OpenTelemetry traces
Every step, tool call and LLM invocation emits an OTEL span. Ship to Grafana, Honeycomb, Datadog or your own collector.
Cost caps
Set token budgets and cost limits per invocation. Agents stop gracefully instead of burning quota on runaway loops.
Model-agnostic
Swap the backing LLM without rewriting the agent. Supports OpenAI, Anthropic, local models via Ollama, and any OpenAI-compatible endpoint.
Eval harness
Record production runs as test fixtures. Re-run any agent version against the same inputs to catch regressions before deployment.
Deploy via Hive or API
Deploy agents to a Hive-managed runtime or as dedicated managed endpoints — same codebase, different operational model.
Audit-ready
Every decision, tool call and output is logged with timestamps and attribution. Ready for compliance review without extra instrumentation.
Workloads we're targeting
- ▸Customer support triage, classification and escalation at volume
- ▸Back-office research, data extraction and report generation
- ▸Ops agents that reconcile state across systems on a schedule
- ▸Content and code review pipelines with human-in-the-loop checkpoints
- ▸Long-running workflows that span multiple LLM calls and tool invocations
- ▸Internal copilots that need to read and write real systems via typed tools
Agents + Hive + Hosting
All three layers of the agent stack compose cleanly together. Build and iterate on agents using the runtime, deploy and manage them via Hive, and run long-lived or scheduled agents on Agent Hosting.
Where we're going
-
in beta now
Single-agent runtime
Memory, typed tools, tracing, eval harness. Public API behind the access list.
-
next
Multi-agent orchestration
Named roles, message passing, and shared workspace with auditable handoffs between agents.
-
planned
Evals + replay
Capture production runs as test fixtures. Re-run any agent version against them to catch regressions.
Agents beta is invite-only.
Tell us what you're building — agent type, tool surface, expected task volume — and we'll reach out with access details.
Request agents beta access →Ship an agent on your own infrastructure.
Hive is live today. Agents, Inference, and GPU are in private beta — request access and we'll reach out.