The High-Fidelity AI Collective
A community dedicated to verifiable accuracy in high-stakes AI workflows.
Consistently Reliable and Accurate AI for Forensic or High-Stakes Systems.
We are experimenting with agentic AI systems in high-stakes environments like finance, healthcare and government. The cost of failure is high, and the cost of late failure detection is even higher.
This is what keeps us awake at night:
- Can we make non-deterministic systems reliable enough?
- How do we design systems that can detect AI failures in agentic chains?
- What LLM parameters should we be optimizing for?
- Is prompt engineering effective, and to what extent?
- How do we manage context to ensure consistent attention?
- Benchmarking accuracy and reliability in agentic systems potentially employing n+1 models from multiple vendors?
Our Principles
1. Open by Default
The challenges of high-stakes AI are too great for any single entity to solve. There are many of us working on this use case, and it is wishful thinking to assume that one day hyperscalers will solve it all for us and that their goals align with ours. This is an open space to share knowledge, tools, and discussions in the great tradition of open source.
2. Contribution is Expertise
We value practical knowledge and working code over credentials. LLM theory is great but here we are focused on practical solutions.
3. Non-commercial
We are not here to sell you anything. This is not an aspiring standards body, not a consultancy, not a vendor. This is a collective of experts sharing what works to improve accuracy and reliability in the field of high-stakes AI workflows.
What Next?
Have a look at our posts to see if there's anything that interests you. The site is powered by GitHub, you can contribute by forking the repo and creating a pull request.
If that is a bit much, why not lurk a bit in the discussions?