An agent that scores well on your task benchmark can still delete the wrong file, close a ticket it should have escalated, or push a change…
Most teams ship an MCP agent to production the same way they ship a feature: it passed the demo, the tests are green, and someone says "look…
The model at the top of the leaderboard is not necessarily the model you should ship. Leaderboards rank one axis, task score, on someone els…
OpenRouter's Ori Eval is the most credible self-serve agent eval we have seen ship this year, and it valid…
Public MCP benchmarks cannot tell you whether your agent picks the right tool from your MCP servers. They test generic, fixed toolsets under…
Scoring only the final answer of an agent is dangerous. An agent can return the correct result while calling the wrong tool, retrying five t…
Independent LLM evaluation is when a separate party, with no stake in the outcome and no exposure to your test data during training, grades…
Benchmark contamination is when benchmark data leaks into a model's training data, so the model has effectively seen the test before taking…
There is no best LLM. There is only the best model for a specific job, measured on your task, through your harness, against your budget. So…
Yes, the harness affects LLM performance, and it affects it a lot. You do not ship a model. You ship a system: a prompt, an agent loop, tool…
LLM-as-a-judge is reliable, but only when you control for its known failure modes. Used as a raw scorer it inherits three documented biases…
pass@k is the probability that an agent succeeds on at least one of k tries. pass^k is the probability that it succeeds on all k tries. That…
A demo tells you an agent can do a task once. Production asks whether it can do the task a thousand times unattended without a costly mistak…
Use a public benchmark to survey the field and shortlist models. Use a private eval to decide what you ship. A benchmark is a shared public…
Contamination-free LLM evaluation means testing a model on data it could not have seen during training. If your evaluation set overlaps with…
You can run a rigorous LLM evaluation without a single row of production data leaving your network. That is what in-VPC LLM evaluation means…
Build in-house for your development loop. Buy eval as a service for independent, contamination-free, regulator-acceptable validation. Most t…
Run every vendor through one identical exam built from your own data, score it blind, and report results with error bars. That is the whole…
Independent model validation for banks means a party outside the model's development team confirms that an LLM or agent does what it claims,…
You do not need four evaluations to satisfy four frameworks. You need one rigorous evaluation, run once, whose artifacts you map to SR 11-7,…
EU AI Act model evaluation requirements come down to one thing you can act on: if your AI system falls in a high-risk category, you have to…
RBI FREE-AI compliance is not a certificate you buy. It is evidence you produce. For an Indian bank deploying LLMs or agents, the practical…
If you run AI in more than one jurisdiction, you do not need a separate evaluation for each regime. You need one independent, contamination-…
UK AI model validation means showing, with evidence someone outside your build team can check, that your LLMs and agents do what you claim o…
If you run AI in a Singapore financial institution, you validate LLMs and agents by producing evidence that maps to the MAS FEAT principles…
OSFI E-23 model risk management applies to the LLMs and agents you deploy, not just to credit scorecards and capital models. If your institu…
Australia AI governance model risk comes down to one question a regulator or auditor can ask: can you show, with evidence, that your LLM or…
UAE AI governance model validation means you can show, with evidence, that an LLM or agent was tested for the job it does, by a party indepe…