For Engineering leads with reliability pain
APIs & durable systems
We build long-running operations that survive restarts, retries and partial failure, using Temporal for durable execution. When a step fails at three in the morning the workflow resumes from where it stopped rather than from the beginning, and the full history of what happened is available afterwards.
Long-running operations that survive restarts and partial failure. Temporal under the lakehouse jobs, agent runs and approvals that must not half-complete.
5 common questions, answered below ↓Temporal turns a fragile chain of API calls into a workflow with history. When a step fails at three in the morning, the workflow resumes from where it stopped rather than from the beginning, and you can read exactly what happened.
- Durable workflows with complete, replayable execution history
- Compensation and rollback paths designed in, not bolted on
- Human-in-the-loop approval gates that survive process restarts
- Migration of existing job chains onto durable execution
How an engagement works
01
Talk to an engineer
A real conversation about your initiative with a senior engineer who has built this before. Not a sales call. What you are trying to build, what has been tried, and what is realistic.
02
Discovery and scoping
Two to three weeks to clarify requirements, evaluate where AI fits, and define realistic scope. On AI work this is also where success gets defined precisely enough to score, because a goal nobody can measure cannot be hillclimbed. You get a plan you can act on before committing to a larger engagement.
03
The right team, daily demos
We put the team the work actually needs on it and show you running software every day. Built with the same rigor as any enterprise system: tested, monitored, documented.
04
Production and beyond
Deployed and running under real load, handling real business processes. Ongoing support and team continuity for whatever comes next.
Also on this site
Expertise pages that sit under this line.
Migrations to Databricks
Off Snowflake, Synapse, Teradata and SQL Server, onto Lakehouse and Lakebase, with a cutover you can reverse.
Data engineering
Pipelines that hold, tables people trust, and a bill that stops surprising you.
Data science & AI
Context stores, memory, retrieval and governed agents that survive production.
AI/BI & Genie dashboards
Genie answers a business question in English, and the answer holds up when somebody checks it against finance.
Machine learning
Models that reach an endpoint, get retrained on a schedule, and can be rolled back by somebody who was not there.
Data & AI governance
Unity Catalog designed so grants hold, lineage survives a refactor, and an agent inherits permissions instead of routing around them.
Forward-deployed teams
Product, design and engineering people who sit inside your business, find the real problem, and ship it.
Product development
Full product delivery: multi-tenant architecture, operator consoles and the data layer under them. Shipped as Databricks Apps when the product belongs next to the lakehouse.
FAQ
APIs & durable systems, answered
What problem does durable execution actually solve?
Any process with more than a few steps that must not half-complete: a payment that charges but does not fulfil, a repossession that starts but is never recorded, a pipeline that dies mid-run and leaves partial data. Temporal makes the workflow itself durable, so the process survives the infrastructure under it.
Do we have to rewrite our services to use Temporal?
No. The usual pattern is to leave the services alone and put a workflow in front of the sequence that calls them. Your existing APIs become activities. That is how we migrate an existing job chain without a rewrite.
How is this different from a queue and retries?
A queue gives you delivery. It does not give you the state of a business process. Temporal keeps a complete, replayable history of the workflow, so you can answer what happened, where it stopped and what compensating action ran, without reconstructing it from logs.
Can a human approval sit in the middle of a workflow?
Yes, and it survives a restart. A workflow can park for days waiting on a signal, then continue from exactly where it stopped. We use that pattern in our own systems for anything that leaves the workspace.
Do you work with Temporal Cloud or self-hosted?
Both. TechFabric is a Temporal partner and we have certified durable paths against Temporal Cloud, including a workflow that survived a full application restart and completed from its original history.