xval.ai builds forecasting models, LLM applications and data platforms for companies that need results, not headcount. Our engineers own the spec, the acceptance scenarios and your outcome. AI agents write, test and ship every line of code. Fixed scope, fixed price, no surprises.
You leave the call with a scoped proposal or a straight “this is not a fit”. Either way, no cost.
Production systems, not slide decks. Every engagement ends with code running in your environment.
Demand, churn, risk, pricing, maintenance. Models trained on your data, validated on holdouts you control, deployed as an API or batch job you can call on Monday.
Document processing, retrieval over your knowledge base, and agents that execute multi-step workflows. Grounded in your data, with evaluation suites so you can trust the answers.
The plumbing that makes the models possible: ingestion, cleaning, feature stores, dashboards. Built to run unattended and hand over cleanly to your team.
Traditional teams scale with people. A software factory scales with compute. That is why we can quote in days and deliver in weeks.
We turn your problem into a written spec and a set of acceptance scenarios: concrete inputs, expected outputs, and the metric that means “done”. You sign off before anything is built.
AI agents write the code, the tests and the infrastructure. A validation harness runs the scenarios thousands of times and the agents iterate until the results converge. Our engineers watch the metrics, not the diffs.
You receive the running system, the source, the harness and the documentation. Deployed in your cloud or ours, owned by you, with a handover session for your team.
Small, fixed-price steps. Each one leaves you with something you own, whether or not you take the next.
We audit your data and the problem, write the spec and the acceptance scenarios, and give you a fixed-price quote for the build. If you stop here, you still own a spec any team can execute.
The factory grows the system against the scenarios you approved. Weekly demos on real data. You pay on milestones: kick-off, mid-point, acceptance.
Monitoring, retraining, new scenarios as your business changes. The harness keeps running, so improvements ship without regressions.
Bring the problem and a sample of the data. In 30 minutes you will know whether it is feasible, roughly what it costs, and how long it takes.