Scenario
A YAML manifest plus persona files: places, population, time model, budget, questions. Versionable, diffable, generatable.
The Platform
A single agent scales to the edge of its context window. An organisation scales through roles: own context per agent, communication over events, knowledge in shared memory. HiveWeaver is the substrate for that.
Three layers, clear contracts: you describe a world, plugins provide its behaviour, the engine carries both — and never changes per scenario.
A YAML manifest plus persona files: places, population, time model, budget, questions. Versionable, diffable, generatable.
A .NET library with places, tools, decision strategies and metrics. Domain knowledge lives here — persona- and role-neutral.
An Orleans cluster of virtual actors: agents, places, simulations. Memory, audit, approvals, budget and replay are engine features.
Every agent decision is a thought — an auditable tree instead of a black box:
An event in the place, a heartbeat, a directed message — or nothing, in which case the agent keeps sleeping.
The relevant place state plus recall from episodic and semantic memory — bounded and logged.
Deterministic strategy, LLM choice or hybrid — the model provides content, the control flow stays yours.
A tool call with a declared side effect: mocked or real, approval-gated where needed — always in the log.
The chain runs autonomously upwards until it hits something it cannot decide itself — then it escalates with a decision-ready summary. Approvals, budgets and audit make that dependable.
The strongest reviewers aren't LLMs at all: test runs, builds, deterministic fact checks. Where LLMs review, fresh context and adversarial framing keep the gate from being theatre.
Dev department, radio station, research team, underwriting desk — the same primitives: roles, places, events, memory, governance. The domain is a scenario, not a fork.
One command installs the project templates for scenario and plugin.
The template generates a manifest, a persona and a mini plugin with a first tool.
One command brings up the whole environment — database, messaging, engine, API, dashboard.
The validator checks the manifest against the loaded plugins; then the simulation starts.
Follow in the terminal or in the Studio: cockpit, pulsing world graph, timeline, social feed.
Verdict as Markdown or JSON, inspect the thought log — and chat with the report to dig deeper.
The second path is even shorter: upload documents, state your question — the scaffolder builds the scenario.
91 commands, each with JSON output for CI and scripts — from starting a sim to searching thoughts.
Live cockpit with sim clock and cost per hour, world graph, prediction report, agent interview — declaration-driven, no per-domain UI code.
API-first: the API is the only way into the engine; CLI and Studio are just clients. Live streams via SignalR and SSE.
Your AI assistant drives HiveWeaver via MCP; agents talk to external agents over A2A.
The publicly audible showcase — an independent product that consumes HiveWeaver like a customer, through the API.
To the showcaseDeterministic, hierarchical retrieval over your document corpus — the agents' shared knowledge.
The CQRS/identity framework beneath the API, and the frontend platform the Studio runs on.
HiveWeaver is released as open source under the Apache License 2.0: free to use — commercially too — with an explicit patent grant. Self-hosting is an explicit part of the design — all the way to fully local operation without a cloud LLM.
.NET 10 · Orleans · Aspire · PostgreSQL + pgvector · Redis · RabbitMQ · OpenTelemetry — a production stack, not a research script. 4,000+ tests keep it honest.
HiveWeaver is in pre-launch: source code, Docker images and a CLI will be published — preparation is under way, and a SaaS offering is deliberately not planned. If you have a use case — simulation, automation or both — we'd love to talk about it: the contact form is the shortest route.