Research Lab

AI agents that get
better every day

We are a research lab building the methods that make AI agents learn from their own experience - improving performance, cutting cost, and enabling full data privacy.

AI agents hit a wall before becoming productive

Unreliable performance, sensitive data concerns, rising model costs. We solve all three.

Performance

Higher success rates, fewer human escalations, better decision quality

Cost Reduction

Intelligent model routing and small model distillation. Lower cost per request, lower latency

Privacy

Data never leaves your organisation. Vendor independence and regulatory compliance

The Learning Flywheel

Analyse

Understand your workflows

Setup

Configure agents & tooling

Deploy & Collect

In production

Train & Improve

RL, distillation, ICL

Onboarding

Continuously Learning

Ready to make your AI agents learn?

Get in Touch

Our Offering

What’s holding your AI agents back?

Identify your challenge below. Then see how we solve it.

“My agents aren’t reliable enough”

Wrong decisions, constant escalations, inconsistent quality. They should be getting better - not staying stuck.

“My AI costs keep growing”

Expensive API calls, oversized models for simple tasks. Scaling up means paying more - with no efficiency gains.

“I can’t use external AI APIs”

Sensitive data, regulatory requirements, vendor lock-in. You need AI that runs in-house.

How we solve it

Agents that learn by doing

Core
↑ Performance ↓ Cost Privacy

Your agent practices in a real or simulated environment - improving with every iteration.

Learn from your existing logs

↑ Performance ↓ Cost Privacy

No simulator? We build a training world from your data, then run RL on it.

Agents that remember and adapt

↑ Performance

User corrections and system feedback flow into the agent’s memory - immediate improvement, no retraining.

Use cheaper models where possible

↓ Cost

Automatically route easy requests to smaller models. Same quality, lower bill.

Your own compact expert model

↓ Cost Privacy

Compress frontier-model knowledge into a small model you own and run yourself.

Everything on your infrastructure

Privacy

Trained models run on your servers, connected to your tools. Full data sovereignty.

Requires:

Engagement Model

1

Scope

Define target tasks and success metrics together

2

Instrument

Connect to your logs, traces, or environments

3

Train

RL, distillation, or routing - whichever fits

4

Deploy

Ship improved models, monitor, repeat

Ready to make your AI agents learn?

Get in Touch

Projects

Projects

Our work bridges reinforcement learning research and real-world deployment.

Coming soon, stay tuned.

Contact

Challenge Us

What's the AI problem you want solved?

Your submission is stored securely on our servers. We'll get back to you within 1-2 business days.

Or email us directly at info@aganthos.com