In-product copilot
Help users get more done inside your product.
- 1Grounded in each customer's data
- 2Takes allowed actions
- 3Measures quality and cost
Austin, TX · Generative AI Engineering
Generative AI for Austin teams: in-product assistants, engineering search and public service answers, grounded in your data and tested before release.
Generative AI Engineering in Austin
Austin pairs fast-growing software companies with semiconductor fabs, state government and a growing health sector. Texas now has its own AI governance law on top of its privacy act, so AI plans here need to account for both.
Where it fits
Help users get more done inside your product.
Find past failure analyses, specs and procedures.
Clear answers from official guidance, with sources.
Built for Texas rules
Consent for sensitive data and assessments for high-risk processing.
Prohibited AI uses, with added duties for government AI.
Controlled technical data kept away from tools and people it may not reach.
Safeguards and a business associate agreement for anything touching patient data.
Working together · Central Time
Your morning is our evening, so we meet live at the start of your day and build while you sleep.
How we work
We agree what a good answer looks like and build a test set.
We connect trusted sources and design retrieval around them.
We measure accuracy, safety and cost, and iterate until it holds up.
We launch with monitoring and feedback loops that keep it improving.
Yes. We can host models or use managed model services inside your cloud account, keeping data within your security controls.
Answers are grounded in your approved sources, linked to them, and tested against a set of real questions before launch and after every change.
Retrieval-augmented generation (RAG) finds the most relevant passages in your own content and gives them to the language model with the question, so answers are grounded in your data and can cite their sources.
Often not. Good retrieval and prompt design solve most enterprise use cases. We recommend fine-tuning only when evaluations show it clearly improves quality, cost or speed.
We design around your security requirements: private deployments where needed, access controls applied to retrieval, no training on your data without consent, and full logging.
Let's talk
We help you navigate Enterprise AI, from first use case to production.
Let's connect