Cut your AI spend. Not your AI capability.
Managed memory architecture that delivers better results at a fraction of the token cost — with data sovereignty built in.
Start from a template
Each template comes with a tailored identity, curated tool selection, and sensible defaults. Everything stays editable.
Office Support
A general assistant for the office. Joins communication channels, assists employees with tasks, and supports business processes through documentation and dispatching.
Community Management
Manage community channels. Monitor public sentiment and market trends, handle moderation, field questions from customers, automate public communications.
Research Assistant
Organize research projects. Conduct market research, monitor financial markets, analyze performance metrics, make predictive analyses.
Your AI bill is proportional to context size.
Every API call processes the entire context window. The industry's answer to "the agent forgot something" is to make the window bigger — a million tokens, two million tokens. But every token in that window is processed and billed on every single call. For a company with thousands of employees using AI daily, this is the single largest line item in the technology budget.
And the bigger window doesn't even help. Research consistently shows that models degrade with more irrelevant context — the "lost in the middle" effect. Doubling the context doesn't double the quality. It often reduces it.
You're paying more for worse results.
How Animus manages context
Instead of dumping raw history, Animus runs a curation pipeline that injects only what matters.
Capture
Every interaction — conversations, tool results, decisions, outcomes — is recorded as structured episodic memory across temporal layers (day, week, month, year).
Consolidate
An automated pipeline promotes valuable knowledge, merges duplicates, retires stale facts, and builds cumulative understanding. Configurable consolidation schedules.
Assemble
When the agent acts, embedding-based semantic retrieval selects only contextually relevant knowledge. A focused, curated prompt — not a raw dump of everything.
The result: each API call processes 15–20K tokens of curated, relevant context instead of hundreds of thousands of tokens of raw history. Lower cost per call. Better signal quality. Agents that improve over time instead of getting more expensive.
Built for organizational deployment
One deployment. Thousands of agents. Complete control.
Order-of-Magnitude Token Reduction
Curated context injection means each API call processes only what's relevant. For high-volume deployments, this translates directly to proportional cost savings on your LLM provider bill.
Multi-Tenant by Design
Thousands of agents on a single deployment. Each with its own provider, model, tool permissions, memory spaces, and channel bindings. Per-agent policy and identity — no shared state.
Self-Hosted, Air-Gappable
Runs entirely on your infrastructure. Use local models via Ollama for complete network isolation. No data traverses third-party servers unless you explicitly configure it.
Auditable and Extensible
Apache 2.0 source code. Tool calls, LLM interactions, and memory mutations are traceable through the kernel's diagnostic output. Embed Lua scripts for custom workflows. Add providers without touching the kernel.
Sandboxed Tool Execution
Default-deny file access, SSRF-protected HTTP client, shell command allowlists. Agents can't access what you don't explicitly permit. Per-agent permission scoping.
EU Data Compliance
Made in Europe. Self-hosted means GDPR-friendly by architecture — data never leaves your jurisdiction. Compatible with EU AI Act sovereignty requirements.
Codified Procedures
Install standard operating procedures from a shared repository. Agents learn organizational workflows — onboarding, compliance, incident response — and apply them consistently. Connect your own SOP repository for team-specific procedures.
Data sovereignty by architecture.
Animus is self-hosted software. Your agents, their memory, and all operational data live on your infrastructure — not on a third-party SaaS platform. No data leaves your network unless you explicitly configure an external LLM provider. Use local models (Ollama) for complete air-gapping, or route to the provider of your choice.
Apache 2.0 licensed. Made in Europe. No vendor lock-in, no proprietary data formats, no cloud dependency. The software is auditable, modifiable, and yours.
Ready to reduce your AI costs?
Deploy in minutes. One binary. Embedded admin UI. Runs on your infrastructure.