Veso Labs: Generative AI Software Development
Veso Labs builds custom AI solutions and pioneers open techniques. We deliver generative AI software, integration, and LLMOps for your specific needs.
Our Approach
We approach each veso labs: generative ai software development engagement around practical business outcomes and responsible AI. We work closely with your team to understand the real requirements and deliver solutions built for your challenges, not a template.
We build on current Generative AI with a firm commitment to data protection and privacy. Honest assessment, clear planning, and senior engineering see GenAI integrated into your business and running in production, ready for your team to operate.
Key Features
- 01
Open techniques, code, and technologies
- 02
GenAI integration
- 03
LLMOps
Engagement
How a Veso Labs build runs
- 01
Understand the problem
2 weeks
We work through your flows, data, and integrations until we know exactly what to build. You leave with a clear plan and a clear price.
- 02
Build it
8–16 weeks
We build in short cycles with a working demo every week. You see real, running software from day one. You can change direction whenever you need to.
- 03
Make it real
2–4 weeks
We connect it to your systems and test it with your team until it holds up. Nothing surprises you at handover.
- 04
Hand it over
1–2 weeks
Documentation and a clean handover to your team, so they can run it without us. We stay if you want us. We leave when you do not.
What good looks like
Working software, in production, without the guesswork.
~12 weeks
To working software
From first conversation to something running in production. Bigger builds ship in stages, with a working demo every week.
Model-agnostic
Claude, GPT, Gemini, open-weights
Selected by task, residency, and cost. Never vendor preference.
Production
Built to operate
We hand over working software your team can run and maintain.
FAQ
Veso Labs frequently asked questions
Do you build new products or extend our existing systems?
Both. Most engagements layer GenAI onto an existing system of record through durable contracts. Greenfield or not, we ship working software your team can run from week one.
How do you handle model selection?
We architect against an evaluation harness, not a single vendor. Frontier models (Claude, GPT, Gemini) and open-weights stay swappable behind the same contract, selected per task by latency, cost, residency, and quality.
How is the build priced?
We spend about two weeks working out exactly what to build, then tell you the price and the scope before anything starts. Any change is agreed with you up front. You are never billed by the hour.
What do we get at the end of the build?
Working software your team can operate, with documentation and training, handed over cleanly. Ongoing support is optional, never a precondition. We stay if you want us and step back when you do not.
How do you measure quality of a generative AI feature?
Every build ships with an evaluation harness: labelled cases, automated scoring, regression checks. Quality becomes a number we track over time, not an anecdote from the demo.
Next step
Three ways to start the conversation.
Book a strategy call if you have a concrete problem in mind. Otherwise, our research and engineering writing is the fastest way to see how we think before you commit to a meeting.