Solutions · Products

By product.

Generative AI software, built for operators.

Where a packaged product solves the problem better than a custom build, that is what we ship. Each product earns its place by surviving real workloads, runs self-host or SaaS, and stays model-portable underneath.

Our product thesis

Products earn their place when a packaged surface ships faster than a bespoke one — and not before.

The suite stays narrow on purpose. Each product is a problem shape that recurs often enough to justify a packaged answer. Where the shape does not recur, we route into Veso Labs as a service engagement instead — the product/service boundary is decided per engagement, not by sales tactics.

The suite

Four products, each a problem shape that recurs across our engagement portfolio.

How we ship product

Three claims that hold across every product in the suite.

Production-grade

Not demoware

Each product earns a place in the suite by surviving real customer workloads — not by looking good in a slide.

Self-host or SaaS

Deployment optional

Run in our cloud or inside your VPC. Same product surface, your data perimeter.

Vendor-agnostic

Model-portable

Underlying model providers are swappable per workspace. The product logic survives the model churn.

FAQ

Products — common questions

How does a Veso product differ from a Veso service engagement?

A product is a packaged piece of software with a defined surface — install, configure, use. A service engagement is custom delivery that builds for your specific data, integrations, and constraints. Most clients use both: a product where it fits, custom work where it does not.

Can products be deployed inside our own infrastructure?

Yes. Every product ships with a self-host path alongside the managed SaaS option. Customers in regulated industries — financial services, healthcare, legal — typically self-host inside their own VPC with their own model endpoints.

Are products tied to a specific model provider?

No. Model providers are swappable per workspace. A self-hosted deployment can run against Anthropic Claude, OpenAI GPT, Google Gemini, or self-hosted open-weights models (Llama, Mistral, Qwen). The product logic is designed to survive model-vendor churn.

Can a product be extended or integrated into existing systems?

Yes. Every product exposes a typed API for integration; most have published webhook and SSO contracts. For deeper customisation we route into Veso Labs as a service engagement — that is the path when the requirement crosses the product boundary.

Next

Need a custom build, or want to see a product against your own data?

Book a demo on the product that fits, read how we evaluate the underlying models, or talk to us about a Veso Labs build where the requirement crosses the product boundary.