Self-hosted AI operations platform

The right software for your agents.

AI agents don't need another chat window — they need a workplace. A project board, real tools, and 14 guardrails that verify the work before it ships.

runs on your infrastructure · your data never leaves · 12 model providers

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guardrails
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specialist agents
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model providers
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tests
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% self-hosted
The problem with chat

Chat is where work disappears.

Twenty agent terminals and nobody knows what shipped. The model says it did the thing. Did it? The answer is somewhere in a transcript no one will read again.

Work you can't find isn't work. It's conversation.

01
How it works

Assign it. The team works it. You review it.

Exolvra runs your AI team the way you run a human one — through a project, not a prompt.

Assign work

Drop a goal on the board. The Project Manager agent decomposes it into issues, sets dependencies, and assigns the right specialists — overnight, on a heartbeat.

goal → 5 issues · APEX-15…19
deps linked · 2 clarifying questions asked

The team executes

Eighteen specialists work with real tools — shell, browser, code, design canvas, your integrations. Every turn passes through 14 guardrails; weak work is bounced back and re-driven until it passes.

guardrail: substance ✕ → revised → ✓ pass
tools: web_search · data_store · browser

Verified work lands

Results arrive for human review with the receipts — what ran, what it cost, what passed. Code lands as pull requests. Every action is in a hash-chained audit log.

PR #214 opened · checks
audit: 142 entries · spend $3.84
02
Why not a chat app

Everyone gave agents a chat window. We gave them a workplace.

A chat window

how most agent products work
  • You prompt; it responds; you hope
  • Output buried in scrolling transcripts
  • "Looks busy" is indistinguishable from "did the work"
  • Multi-agent means more chat windows
  • No record your auditor would accept

A workplace

how Exolvra works
  • Work is assigned on a project board, with owners and due dates
  • Output is a deliverable — a document, a design, a landed PR
  • 14 guardrails verify each turn and re-drive weak work
  • Multi-agent means a team — a PM that delegates, specialists that execute
  • Everything is audited — hash-chained, in-transaction, exportable
Inside Exolvra

This is where your agents work.

The board they work from, the team at a glance, and a project in motion.

exolvra · issues
The Exolvra Issues board — every tracked piece of work across agents and teams, with status, assignee, and progress every issue, owned
exolvra · agents
Your agents at a glance — specialist cards with workload, spend, and model the whole team
exolvra · project · product launch q2
Inside a project — overall progress, work columns, needs-attention queue, spend forecast, and reliability for Product Launch Q2 inside one project
03
The platform

Everything a working team needs. Nothing leaves your network.

01

Guardrails that re-drive

Substance checks, anti-generic-content, completeness scoring, visual verification for design work — 14 gates that bounce weak output back to the agent automatically. No acknowledgment theater.

02

A PM that runs the board

Goals decompose into issues with dependencies that auto-unblock. Backlog triaged overnight. Stale work gets nudged every 30 seconds by a heartbeat watchdog.

03

12 providers — including your CLI subscriptions

Claude, GPT, Gemini, Mistral, Groq, Bedrock, Azure, Copilot, local Ollama & LM Studio — plus Claude Code and Codex connected as native backends, from the web UI, even in containers.

04

35 integrations, one click

Notion, Linear, GitHub, Slack, Stripe, HubSpot and more from the MCP Library — with per-agent allowlists, so the BDR agent never touches your repo. Plus 70 bundled skills and 35+ native tools.

05

Governance your security team will sign

SQLCipher + AES-256-GCM at rest. Secrets substituted at the wire — {{secret:NAME}} never enters a prompt or log. Hash-chained audit written in the same transaction as the action. Approval workflows, budgets, work hours.

06

Work that lands with receipts

Reviewed issues, landed pull requests, published internal apps with versions and rollback. Every deliverable traceable to its goal, its agent, its cost, and its gate verdicts.

The team

Eighteen specialists, day one.

Pre-installed and ready for assignment — or design your own.

Project Manager Research Analyst Code Assistant DevOps Designer Data Analyst Head of Product Chief of Staff App Builder Creative Writer Sysadmin Sales BDR Recruiter Investment Analyst Graphic Artist Wiki Editor Home Assistant Exolvra Assistant

+ a five-persona Council for high-stakes review · + unlimited chatbots you design

04
Your infrastructure

Your AI team. Your servers. Your data.

  • One container or one signed install. Docker, Podman, or the Windows desktop build — with a first-run setup wizard.
  • Air-gap capable. Run fully offline with local Ollama or LM Studio models. Nothing leaves.
  • Bring your own keys. Flat platform pricing — your model bill is yours, with budgets and rate tracking per agent.
  • Built for the review. Encryption at rest, audit chain, RBAC, and — by design — no repo-supplied shell hooks.
exolvra · mission control
Exolvra Mission Control — morning brief with approvals waiting, issues in flight, spend, and the approval inbox
05
Pricing

Pay for the platform. Not per token.

Trial
Free
7 days · full product

The whole platform, on your own hardware. No credit card.

Pro
$49
per user / month

For the team inside the team. Full platform, all providers.

Team
$149
per user / month

Governance depth — approvals, budgets, audit export, priority support.

Enterprise
Custom
annual

Air-gap, Postgres HA, compliance reviews, and a human who answers.

BYOK on model costs — Exolvra never marks up inference. Cloud edition coming Q3 2026.

Questions

Asked by every security review so far.

Is it really self-hosted?

Yes — one container, one signed desktop install, or one binary. An optional Cloud Mode further restricts agents to network + memory only. There is no required call-home in the work path.

What data leaves my network?

Only the LLM API calls you configure. Point it at local Ollama or LM Studio models and nothing leaves at all.

How is this different from a chat assistant?

You assign issues on a project board; a PM agent decomposes them; specialists execute; 14 guardrails verify before anything lands. Work is managed and reviewed — it doesn't disappear into a transcript.

What happens when an agent fails?

Guardrails re-drive weak output automatically. Infrastructure failures retry; agent-side failures surface cleanly. A heartbeat watchdog sweeps for stalled work every 30 seconds, and nothing closes a goal-linked issue without passing its gates.

Which models can it use?

Twelve providers: Anthropic, OpenAI, Google, Mistral, Groq, AWS Bedrock, Azure OpenAI, GitHub Copilot, Ollama, LM Studio, CommonStack — plus Claude Code, Codex, and Gemini CLI connected as native backends, so the subscriptions you already pay for become your agents' engines.

Is it open source?

No — Exolvra is a commercial product with a free 7-day full-product trial. That's deliberate: the governed, packaged, certifiable layer is the product.

Get access

Give your agents a place to work.

Join the waitlist — we're onboarding teams in order.