Try our Prompt Optimizer to automate prompt engineering!

Launch trustworthyAI apps in weeks

The fastest way to make your prompts, RAG and AI agents more reliable.

Iterate faster during development and prevent regressions in production.

We benchmarked Claude 3.5 Sonnet (new), GPT-4o, Llama 3 & Google's Gemini's models on code related tasks.Read our arXiv paper here.
Launch YC: 🚀 Hamming - Let AI optimize your prompts (free for 7 days)

Build a self-improving system

Multi-step RAG & AI agents are hard to get right. A small change in prompts, function call definitions or retrieval parameters can cause large changes in final LLM output.

Our vision is helping product and engineering teams build self-improving AI-systems that require minimal human oversight.

Prompt Optimizer

Writing prompts by hand is slow and tedius. Use our prompt optimizer (free to try) to automatically generate optimized prompts for your LLM.

Save 80% of manual prompt engineering effort.

Hamming Datasets

Leverage our curated adversarial datasets aimed at testing your AI app's robustness against prompt-injection attacks.

Curate golden datasets with built-in versioning.


Test your pipeline's performance on each dataset using our collection of in-house scores that measure accuracy, tone, hallucinations, precision and recall.

We create custom evals unique to your use-case aligned with your preferences.

Active monitoring

We go beyond passive monitoring. We actively track and score how users are using your AI app in production and flag cases that need your attention.

Easily convert traces into test cases and add them to your golden dataset.

First-class support for RAG & agents

RAG systems can fail during retrieval or reasoning. Use our RAG optimized scores to quickly identify bottlenecks in your pipeline.

Function calling is hard. We make it easier to stress-test function calling in your agents.

Easy collaboration

Easily annotate examples by hand when human supervision is necessary.

Share experiment results and production traces with your team.

Trusted by AI-forward enterprises

Yossi Eliyahu
Yossi Eliyahu
VP of Engineering @ Fora
There are a lot of low quality AI apps out there. We care a lot about quality. Hamming helps us launch accurate, robust and resilient AI apps that our users love.
Chris Chen
Chris Chen
PM @ Fora
Hamming allows me to test new changes to my AI pipeline 100x faster than vibe checking.
Mark Wai
Mark Wai
Co-Founder & CTO @ Inkly
At Inkly, we're building the modern legal experience for startups using GenAI. Being able to test our system against a dataset of test cases gives us a huge peace of mind and clarity on where we need to improve.
Conner Swann
Conner Swann
Co-Founder @ Intuitive Systems
The team is tackling a huge pain point for me - running evaluations continuously while I'm fine-tuning custom models.

Eliminate hallucination → Drive retention

We're experts in supporting companies tackling high-stakes domains where getting the wrong answer leads to high churn or regulatory consequences.

Our customers use Hamming to build retentive AI products in their industry.

Built for teams

Our platform scales with you

Building reliable AI products is a team effort. Hamming is built to support cross-team collaboration.

ML Engineer
ML Engineer
I love the ability to debug my RAG pipeline on a one-off basis.
Data Scientist
Data Scientist
I love being able to understand the reasoning behind why the AI judge picked a specific score.
Product Engineer
Product Engineer
This is like Optimizely for building AI products.
DevOps Engineer
DevOps Engineer
We catch regressions before they reach users.

Experiment Tracking

For each experiment, track your hypothesis, proposed changes and learnings.

Manual override

Override AI scores. Every override aligns the AI judge with your preferences.

Dataset versioning

Any change to the golden dataset triggers a new version. Teams can compare experiment results on an apples to apples basis.

Powerful Search

Search across all traces and quickly root-cause why your AI system produced a particular answer.


AI pipelines are non-deterministic. You can run multiple runs for the same experiment - visualize performance distributions and isolate flake tests.


Share datasets, experiment results and traces with teammates.


The fastest way to ship AI products with confidence

We've built mission critical data products at
  • Tesla
  • Microsoft
  • Anduril
  • Square
  • Citizen

Use any LLM or vector database

We provide platform-agnostic hooks to evaluate your generation and retrieval steps.