Saabsa · Austin HQ, US delivery
Enterprise AI deployment into the stack you already run
Deployment is not a model endpoint. It is identity, data boundaries, change control, and a system of record that still behaves after the pilot leaves the innovation channel. Saabsa deploys RAG, agents, and workflow AI for US companies that need that path.
The pilot passed. The enterprise did not.
Enterprise buyers stall in the same place: security wants a data-flow diagram, IT wants SSO and an owner, finance wants a cost cap, and the business still has a demo in a side environment. AI deployment services that stop at “we hosted the model” do not clear that review.
Saabsa treats AWS or Azure as the substrate for the AI system. We are not a cloud migration factory, and we will not pretend Kubernetes is the product.
Identity and access
The assistant sees what the user is allowed to see. Service accounts are scoped, not shared.
Integration map
Which APIs are read, which are write, and which writes require a person.
Change control
Environments, CI, and a rollback that does not depend on the person who wrote the prompt.
Operating limits
Latency, spend, and a named on-call path before anyone calls it deployed.
What we deploy
Knowledge assistants over your corpus, agents that call approved tools, document pipelines, and clinic or back-office workflows when a playbook fits. The commercial entry is still the AI Production Sprint, because deployment planning without a scored use case becomes architecture theater.
If the hard part is retrieval, start at RAG development. If the hard part is tool use and approvals, start at agent development. If the hard part is whether you should deploy at all, start at production readiness.
Questions buyers ask
Before you book the sprint
Do you deploy into our VPC?
Yes, when that is the requirement. The sprint states the hosting constraint before a build is sold.
Can you work with our existing model vendor?
Yes. We are not loyal to a single model. Routing and cost belong in the design, which is also how ForgeMeter treats engineering AI spend.
Is this a staff-augmentation contract?
No. You get a named lead and a package. Extra hands are not the offer.
What does “enterprise” mean in practice?
A security review, more than one system, and a buyer who cannot ship a side-channel demo and call it done. Headcount slogans are not the definition.
Related
The rest of the implementation map
AI implementation
Part of the same prototype-to-production path.
Prototype to production
Part of the same prototype-to-production path.
Production readiness
Part of the same prototype-to-production path.
AI agents
Part of the same prototype-to-production path.
RAG development
Part of the same prototype-to-production path.
Enterprise generative AI
Part of the same prototype-to-production path.
Evaluation
Part of the same prototype-to-production path.
Security and governance
Part of the same prototype-to-production path.
Healthcare AI
Part of the same prototype-to-production path.
AI Production Sprint
Part of the same prototype-to-production path.
Bring the prototype, not a wishlist.
The AI Production Sprint is two weeks and fixed fee. You leave with a go/no-go, architecture and security notes, and a next-step quote you can decline.