Swasa Cloud doesn't hand you another AI tool to bolt on. We embed inside your team and wire retrieval, agents, and automation directly into the systems and data you already run on — deployed inside your infrastructure, never routed through someone else's model to get built.
Every engagement moves from diagnosis to a working system to steady iteration — priced and scoped so you know what you're buying at each step.
We map your workflows, data, and systems, and hand back a concrete, buildable spec — not a strategy deck. This is where we find out if there's a real system worth building.
Our engineers sit inside your stack and build the retrieval pipeline, agent, or integration for real — wired into the tools your team already uses daily.
Once it's live, we stay on to tune, extend, and fix — a small monthly retainer instead of a large team you don't need yet.
We wire AI into your CRM, ERP, ticketing, and internal data directly. No new dashboard to log into, no data exported to a third-party app to make it work.
No handoff to an offshore ticket queue. The people who scope the work are the people who build and support it.
You get senior systems expertise on a project basis, sized for a company that can't yet justify a full-time AI hire.
World-class engineering economics let us price embedded work at a fraction of a US or EU consultancy — without cutting engagement depth.
Most AI vendors sell you a plan. We sell you a system that's already running.
Most "AI enablement" runs your data through a third party's model to work. We build the opposite: systems that live inside your infrastructure and never send more than they need to, to anyone.
VPC or on-prem by default. The system runs where your data already lives — not as a hosted SaaS that pulls it out.
Self-hosted open-weight models, or enterprise API agreements with contractual zero data retention — never used to train a third party's model.
Sensitive and PII fields are redacted or tokenized before anything reaches a model call — by design, not as an afterthought.
Every retrieval, prompt, and output is logged and reviewable, so your team can see exactly what the system touched and why.
Code, embeddings, and infrastructure access are handed over at the end of the build — not locked behind our platform.
The system only sees and acts on what a given role is already permitted to touch in your existing tools — no new blanket access.
30 minutes to understand your workflow, your data, and where the pain actually is. No pitch deck.
We audit systems and data on the ground and return a fixed-scope build spec with a clear price for the build phase.
Engineers work inside your stack in short, visible sprints — you see working software every week, not at the end.
The system ships into production. We stay on retainer to tune it as your data and workflows change.
No layers between the person who scopes your project and the person who builds it.
Owns the relationship end to end — scoping, delivery cadence, and making sure the system actually fits how your team works.
Ships the interfaces and integrations that connect the AI system to the tools your team already uses.
Designs the retrieval, memory, and agent infrastructure underneath — the part that determines whether the system actually holds up.
Start with a 30-minute call — we'll tell you honestly whether an embedded build makes sense before you spend anything.