When your app has a great demo but starts hallucinating and fabricating facts in production, that's not a Tuesday — it's a fine, a lawsuit, or a blown investigation.
Chatbots and marketing copy tolerate failure and inaccuracies, but your business can't afford factual errors. If a chatbot points you to the wrong menu, you lose a minute. If you get a citation wrong, it's a fine, a lawsuit, a lost client, or all of the above.
I limit opportunities for the AI to hallucinate. For example, I aggressively prune the chat history and use other context engineering techniques to minimize the chance for hallucination. Enforced tool-use boundaries and structured data with validation also keep the AI honest.
I prevent fabricated facts from getting used. State lives in a database, not in the context window. The model's structured outputs, including tool calls and proposed state changes, are validated against the system's source of truth. Anything that doesn't conform is rejected.
Zoltar is an AI game moderator — a reliability stress test wearing a fun costume. It has to track everything that's happened across a months-long campaign and stay honest about every piece of it. It's forbidden from faking a roll, retconning a fact, or inventing an item a player never earned. That's the same failure class as a fabricated citation or a hallucinated number. I just chose the version where being wrong costs a game night, not a client.
Zoltar works because its state lives in a separate backend database, not in the model's context window. All state changes are validated against ground truth. Bounded retries surface failures outside the model. Tool-use boundaries and structured data constrain the model's output.
I'm a registered patent agent with more than 4 years of patent prosecution experience. I worked inside the process where a wrong word or missing comma has legal consequences. I also have more than 10 years of experience as a software engineer building production systems and applications. I've built systems with high data integrity requirements in trust-critical industries, such as cybersecurity, healthcare, and financial markets.
Start with a system analysis. Let's figure out what's causing hallucinations and where critical data is at risk. Two-week engagement that produces a prioritized remediation plan, for a fixed fee.