Evaluation that improves performance.
Golden datasets and evaluation loops improved core-model accuracy from 60% to 90% for a compliance platform.
For engineering teams
Your team is strong. We make your AI pay off.
Ship better AI, faster. From architecture and experimentation to production, we solve the hard problems alongside your engineers.
Start a conversationHow we'd work with you
- Free, 90 min
We start from your roadmap
A working session with your engineering leads on what is shipping, what is stuck, and where AI specialist expertise will remove roadmap risk.
- Typical: 1–2 weeks
We make what you have measurable
Bring in the right experts, build golden datasets and evals, and measure which approaches work, so quality becomes a number you improve.
- Typical: 2–3 weeks
We make what's stuck work
Custom systems for the critical features you need, built and proven on your own data.
- Typical: 4–6 weeks, then ongoing
We ship it with your team
Integrate, release, and monitor in production alongside your engineers, with the right specialists from our network wherever you need them.
Our Services
AI Evaluation
Golden datasets and eval loops that score every change before it ships.
Production AI Systems
Brittle prompts replaced with multi-stage systems, monitored in production.
AI Architecture
Choose the right models and system design, with benchmark metrics to back it up.
AI Feature Development
New AI features in weeks, built on components proven across 40+ deployments.
Team Enablement
Your engineers build side by side with our ML specialists and PhD researchers.
Value Delivered
- 60% → 90%core-model accuracy for a compliance platform
- 20 out of 20pilot searches matched or beat recruiters at a legal staffing firm
- 1 yearfaster to launch for Edamam, compared with building in-house
Finance Technology Product knowledge in production.
A retrieval agent answers first-line support emails using complex product documentation.
Healthcare Built for Edamam. Owned in-house.
A chat and voice nutrition assistant on Edamam’s data and APIs, with an in-house specialist trained to maintain it.
We've saved an untold number of hours. We're able to make consistent progress on our AI capabilities without having to build out a whole team. [...] Crisp has made the wow scalable.
Questions
- How does Crisp Labs make LLM and machine learning systems reliable in production?
- Crisp Labs builds golden datasets, eval loops and production monitoring, and replaces brittle prompts with multi-stage systems, so every change is scored before it ships. For example, for a Series A SEC/FINRA compliance platform, this approach took accuracy from 60% to 90% and reached 99.98% pipeline reliability across more than 4 million messages a month.
- How does Crisp Labs help with AI architecture and technical roadmaps?
- Crisp Labs helps engineering teams choose the right models, system design, and technical priorities. We review previous experiments, identify the biggest uncertainties, and test competing approaches—so your team knows what to build next and why.
- Can in-house engineers run an AI system after Crisp Labs builds it?
- Yes. Crisp Labs builds alongside your engineers, leaving them equipped to own and improve the system. For example, at Edamam, we built a chat and voice nutrition agent on the company’s APIs and data, and trained an in-house data scientist to run it.