The platform

Build, run and improve governed workflows with your operational context.

Agent Hive gives operations teams a visual way to coordinate specialist agents, connect enterprise systems, and keep review in the loop.

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How to read this page

Two things are different here: the platform works in your domain context, and each agent can improve against recorded evaluations. The orchestration is familiar; the controls make every consequential step reviewable.

Visual-first to build with
Technical depth available underneath
Runs in your own infrastructure

What makes it domain-native

Make every answer specific to your operation

Agents work from your systems, procedures, entities, and constraints rather than generic context. That domain layer is tuned and routed back into the tasks where it improves the result.

01Agents runResponses and tool-calling behaviour are captured as they happen.
02Signal collectedThat behaviour becomes training signal for your domain and your tasks.
03Small model tunedA small language model is fine-tuned on it, rather than prompted harder.
04Routed back inThe tuned model becomes available to the router for the tasks it fits.

Each cycle makes the next set of responses more specific to your domain.

What makes it improve

Measure, change, and measure the agent again

A static prompt drifts as the business changes. Agent Hive evaluates each version against functional tests and records the evidence in the Evals dashboard.

The loop

1
Evaluate
2
Evolve
3
Re-evaluate
4
New version

Every version is recorded, so an improvement has to be shown rather than asserted.

01 · Evaluate
The agent is scored against functional tests across multiple tasks — not a single prompt check, and not a vibe review.
02 · Evolve
What the tests surfaced drives real changes: agent code, instructions, and the harness the agent runs inside.
03 · Re-evaluate
The changed agent goes back through the same tests, so an improvement has to be demonstrated rather than assumed.
04 · New version
A new version is produced and the loop runs again. Every version is a recorded step, visible in the Evals dashboard.

Orchestration

From request to reviewed result

One governed loop carries the objective through context, specialists, reasoning, and review before action.

Stage 1 — Route

Each task is matched to a model and an agent profile — chat, utility, embedding or browser work do not all need the same model.

Capabilities

The working parts your team touches

These are the practical capabilities behind the domain-native and self-improving behavior above.

Visual workflow canvas
Compose the workflow visually, then open the detail when needed.
Drag-and-build composition keeps the first pass accessible, while the underlying configuration remains available for technical review.
Hierarchical delegation
Let each agent bring in the specialist it needs.
Any agent can spawn subordinate agents with their own prompts, tools and permissions. 34 agent profiles ship out of the box, and a research mode adds team formation.
Knowledge-graph memory
Carry context beyond a single conversation.
Entities and relations sit alongside vector recall, so agents can reason about how operational facts connect.
Multi-model routing
Route the right model to each kind of work.
Route across roughly nine provider families per task type — chat, utility, embeddings, browser — and bring your own fine-tuned model in via a provider URL.
MCP, both directions
Connect tools without turning every link into a project.
Agent Hive runs as an MCP client and as an MCP server. Managed OAuth means supported SaaS tools show up as MCP servers without custom integration work.
Evals dashboard
See whether a change actually helped.
Unified, workflow, version and auto-evolve evaluations, surfaced in one dashboard — the record behind every claim that an agent improved.

Trust & governance

Keep data boundaries and decisions visible

Deploy inside the infrastructure and tenancy model your organisation requires. Every run carries the controls, evidence, and approvals a reviewer needs to sign off.

Self-hosted deployment
Run entirely on your own infrastructure via Docker and Docker Compose, in single-tenant mode, with no external OAuth or billing dependency required.
Scoped permissions
Per-agent tool permissions, guardrail agent profiles, filesystem sandboxing, code security checks and secrets masking.
Tenant isolation
Multi-tenant architecture with real isolation between tenants. Roles are scoped to users within a tenant.
Audit logs
Structured, queryable logs of who did what and when, visible to administrators.
Human-in-the-loop, live
Stop, correct or redirect an agent mid-run. An ask-user tool lets an agent request clarification, and approval gates sit on the tool calls that matter.
Tracing & cost accounting
End-to-end tracing at workflow and agent level, with token and cost accounting, visible across tenants.

SOC 2-aligned, externally assessed

Covering sandboxed execution, encryption in transit and at rest, tenant isolation, and full audit logging.

For the engineers on the team

Technical depth is there when you need it

Operations teams can start visually, while engineers retain control over protocols, deployment, and model sourcing. The platform is designed for support and review, not an opaque handoff.

Protocol support

Full MCP support in both directions — as a client and as a server — plus managed OAuth so supported SaaS tools appear as MCP servers without bespoke integration work.

Support for the protocols, not a claim about ecosystem size.