AI system testing,done right.
Sidreon stress-tests your RAG pipeline or AI agent with an independent, versioned suite. We record each run, investigate the failures and show you what to fix—so you can track reliability as your system changes.
by category
top findings and fixes
Invents answers when the documents are silent
Fix: explicit refusal rule, verified by 14 targeted testsSecond source never retrieved on multi-part questions
Fix: raise retrieval depth for 3 topicsCalls the search tool twice for the same query
Fix: cache tool results within a turnAn independent testing partner for production AI.
Sidreon tests RAG pipelines and AI agents for the teams that build them. We find out how your system really behaves, explain why it fails, and give you a clear plan to make it better before it reaches your users.
Our proprietary SDKs run privately in your environment, and our only stake is an honest result.
The team that built your AI shouldn't be the only team testing it.
Builders test the questions they designed for, with the data they already know. That's how a system passes every internal demo and still fails in front of real users. Sidreon comes in with no assumptions, no stake in the result, and one job: find where your AI breaks.
Blind spots
Builders can't test for the cases they never imagined. Those are the ones users find first.
Built-in bias
Tests written by the same people, from the same documents, confirm what the team already believes.
Demo-ready, not production-ready
A great demo proves the happy path works. Production is everything else.
Every way your AI can fail, tested.
From the documents your pipeline retrieves to the last tool call your agent makes. One engagement covers it all, and you don't need to prepare a single test case.
RAG pipelines, inside and out
Does it retrieve the right documents? Does the answer stick to them? Does it admit when the answer isn't there? We test retrieval and generation separately, so you know which one to fix.
Hallucination hunting
False premises, invented entities and questions with no answer. We find out how often your AI makes things up.
Agent behaviour
The right tool, the right arguments, the right order. We check every step an agent takes, not just its final answer.
Adversarial and safety
Prompt injection, goal hijacking and boundary pushing across multi-turn conversations.
Multilingual
Consistent answers across languages, including Arabic, where most testing tools never look.
Root cause for every failure
Every failed test is investigated until we know why: a missing document, a retrieval miss, or the model ignoring what it was given. No unexplained red marks.
Fixes you can act on Monday
Findings ranked by severity, each with a specific change to make in your prompts, retrieval or tools, and the tests that prove the fix worked.
Know what changed. See what held up.
AI outputs can vary between runs, even when the system and prompt stay the same. Sidreon keeps the test cases, suite version and run record consistent, then reports the results with uncertainty in view. That makes regressions easier to spot without pretending every answer is deterministic.
- Versioned test suites you keep and rerun
- Run records preserve prompts, settings and outputs
- Scores include their method and uncertainty
- Repeated checks help separate regressions from run-to-run variation
Not just a score. A plan to improve.
Every Sidreon report tells you what failed, why it failed, and what to change. For RAG pipelines and agents alike.
Confidently answers questions its documents can't answer
Generation: the prompt rewards answering over accuracy
Add an explicit "not in the documents" path, then rerun the 14 unanswerable tests
Multi-part questions get half an answer
Retrieval: the second source never makes it into context
Increase retrieval depth or split the question before searching
Misses products when users call them by a nickname
Retrieval: aliases aren't in the index
Add a synonym map at indexing time
Issues refunds without checking who owns the order
Tool use: a required check is skipped under time pressure
Make ownership verification a precondition of the refund tool
Follows instructions hidden inside a customer email
Prompt injection: tool output is treated as instruction
Separate tool results from instructions and restrict follow-up actions
Loops on search when results are empty
Planning: no stop condition for failed lookups
Cap retries and hand off to a person after two empty searches
Illustrative findings. Your report is built from your system.
Why teams bring in Sidreon.
| Testing it yourself | With Sidreon | |
|---|---|---|
| Independent of the people who built it | No | Yes |
| Tests the cases nobody thought of | Rarely | Yes |
| Expected answers linked to evidence | Depends on the setup | Part of the review |
| Versioned suite and recorded runs | Varies by team | Included |
| Root cause for each failure | Manual digging | Every one |
| Prioritised fixes | No | Yes |
| Agent tool calls checked step by step | Final answer only | Yes |
| Regression checks on every change | When there's time | Built in |
From first call to production-ready.
You keep building. We handle the testing, end to end.
Tell us about your system
A short call about what it does, who uses it, and what can't go wrong.
Connect an endpoint
Our private SDKs run in your environment. No test data or documents required.
We test, end to end
Accuracy, grounding, behaviour and safety, tested from every angle, with every failure investigated.
Fix and retest
Get your report and fix list, make the changes, and rerun the same suite to prove it worked.
Questions teams ask us.
Do we need to prepare test data?
No. Give us access to your system's endpoint and we build the tests. If you already have a test set, we'll use it as well.
Does our data leave our environment?
Our proprietary SDKs run privately inside your infrastructure, against your endpoint. Your documents and conversations stay with you.
Can you test AI agents, or only RAG?
Both. For RAG pipelines we test retrieval and answers separately. For agents we check which tools are called, with what arguments, in what order, and how the agent holds up against manipulation across a conversation.
What does repeatable testing mean here?
We keep the test cases and suite version stable and record each run's relevant settings and outputs. Because model responses can vary, we use repeated checks and report uncertainty where appropriate; a score difference is a signal to investigate, not proof by itself that the system changed.
We already run evals. Why bring in Sidreon?
Because your evals were written by the people who built the system. We bring an independent view, cover the cases your team didn't think of, explain why each failure happened, and tell you how to fix it.
What do we get at the end?
A scored report with its margin of error, every failure explained, findings ranked by severity with specific fixes, and a regression suite you can rerun after every change.
Make sure your AI performs in production.
Find out where your RAG pipeline or agent really stands, and exactly what to fix, before your users find out for you.
Let's put your AI to the test.
Tell us what you're building, what it needs to get right, and when you plan to ship. We'll get back to you to set up a call.