AI evaluation experts, proven on your task
SoReliable AI gives AI teams evaluation experts from the field the model works in. Doctors review clinical answers. Engineers review code. Lawyers review contracts.
Every expert is trained on your task and your standard, then tested on cases with known answers. Only those who pass review your production work.
The problem
General reviewers miss what experts catch
Most evaluation goes wrong in the same place. The output reads well, the checklist is ticked, and the error is one only a practitioner would notice: the drug that clashes with an allergy, the clause that removes a notice period, the test that was quietly weakened.
Automated judges share the model's blind spots, and general raters hit a ceiling on specialist work. If the people grading your model could not do the work themselves, their scores tell you how fluent it sounds, not whether it is right.
What we provide
What you get with SoReliable AI
Domain experts, not general raters
Practitioners in software, medicine, law, science and robotics, matched to the knowledge your task needs.Trained on your standard
We turn your guidelines and edge cases into short training and a check every expert must pass.Proven before production
Experts score real cases with verified answers first. You see how each one performed before they touch your data.Scores with reasons
Every judgment comes with a written rationale, so your team can audit it and your model can learn from it.Agreement you can measure
We track how often experts agree with each other and with the answer key, and recalibrate when they drift.
An example
A clinical summary that passed every automated check
An AI assistant drafts a hospital discharge summary and plans amoxicillin.
Discharge summary
- Patient
- 54, chest infection
- Plan
- Amoxicillin 500 mg, three times a day
- Allergies
- None recorded
- What the checks saw: Automated checks pass: the format is right, the dose is in range, and the note reads clearly.
- What the expert caught: A doctor sees that the patient's notes record a penicillin allergy. Amoxicillin is a penicillin.
The error was invisible to anyone who did not know the medicine. That is the gap an evaluation expert closes.
Illustrative example.
How it works
We prove capability before production
- 1
Define the standard
We agree with you what a correct output looks like, including the hard cases.
- 2
Find and train the experts
We match practitioners to the task and train them on your rubric.
- 3
Prove capability
Each expert is tested on realistic cases with known answers. Only those who meet your bar qualify.
- 4
Evaluate and improve
Qualified experts score your outputs. Disagreements and new failures become new test cases.
Deliverables
What you receive
- Scores against your rubric, item by item
- A written rationale for every judgment
- Per-expert scorecards and agreement metrics
- A catalog of the edge cases your model gets wrong
- Corrected outputs your team can train on
Your rubrics, data, scores and rationales stay yours.
Questions
Questions teams ask
What is an AI evaluation expert?
A practitioner in the field your AI works in, such as a doctor, lawyer or software engineer, who has been trained on your evaluation rubric and judges your model's outputs against it.
How do you check an expert is good enough?
Credentials get someone considered. Performance decides. Every expert scores realistic cases with known answers, built from your edge cases, and only those who meet your standard work on your data.
Which fields do you cover?
Software and systems, clinical and health, legal, science and research, and robotics. If your task needs another specialty, we find practitioners for it.
Who owns the rubrics and results?
You do. Rubrics, datasets, scores and rationales produced for you stay yours, under your NDA and security requirements.
How do we start?
With a pilot on one task: your standard, a small group of experts proven on it, and scores you can check before you commit to more.
Start with one task
A pilot gives you experts proven on your hardest cases, and scores you can check, before you commit to more.
Related
- LLM evaluationSoReliable AI evaluates large language model outputs with experts from your field, against a rubric built from your own quality bar.
- Human evaluation for AI agentsAn AI agent can finish a task, pass the tests and still be wrong. SoReliable AI provides expert human evaluation for AI agents: specialists who review the whole run, not just the final answer.
- Expert data for RLHF and fine-tuningYour model learns from the judgments in its training data. SoReliable AI provides RLHF and fine-tuning data created by experts who know your field.
Ready to try SoReliable?
Tell us what you are building. Any team, any project, any size. We find the specialists, train them on your standard, and evaluate the work against what your project actually needs.