# AI systems that survive the first timeout

> Most AI programmes we are asked to look at already have a working demo. What they do not have is a way to score an answer, a permission boundary, or a process that survives a restart. We build the system around the model, starting from the scoring.

Canonical: https://www.techfabric.com/expertise/ai-ml

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A feature calls a model. A system is everything that has to be true on the hundredth day.

## What we build

- An eval rubric and a test environment before a line of the agent is written
- Context stores and memory that outlive the process
- Retrieval grounded in your own governed data
- durable execution
- Durable execution on Temporal, so a long agent run survives a restart or a deploy

## Questions

### Do you build machine learning models?

When the problem needs one. More often the model is not the scarce part. The scarce part is the system around it: where context comes from, who is allowed to touch what, how you know the answer is still right next month. That work is /services/ai-systems.

### Can this run without our data leaving our environment?

Yes, and that is the default. Applications and agents run in your workspace under their own service principal, inheriting Unity Catalog permissions. TechFabric Harness at /accelerators/harness is how we deploy that agent as a Databricks App.

### What keeps a long agent run from half-completing?

Temporal. We are a Temporal partner and durable execution is what sits under any agent run that takes hours, calls several systems, or waits on a person. The workflow history is the audit trail, so a run that was interrupted resumes rather than restarts and you can reconstruct afterwards what it did. Four systems we have published run on it, including our own. See /durable-execution.

### How do you prove an agent is working?

An evaluation harness with ground truth you own. TechFabric Experiments at /accelerators/experiments keeps that suite running. When the thing being scored is a Genie space, the named engagement is Genie Accuracy at /databricks/genie-accuracy.

### Have you put one into production?

Fabric is a production Databricks App with durable workflows and human approval gates, and we run our own company on it. Canvass, which we built for a client, runs the same way on Cloudflare. Across our clientele, delivery work that needed a team of ten now takes three.