One stack, not four projects.
Production systems where AI, data, cloud and security are designed together from the first commit.
- AI agents, retrieval and data platforms
- Cloud-native product engineering
- Modernisation without a big-bang rewrite
DALLAS, TEXAS · OPERATING WORLDWIDE
Sarsha designs, builds and runs the platforms enterprises depend on — data and AI, cloud and DevOps, cybersecurity, product engineering, modernisation and managed operations.
We design, build and scale systems that make it past the pilot and into production. Engineering discipline, with AI woven through every layer — not bolted on at the end.
One stack, not four projects.
Production systems where AI, data, cloud and security are designed together from the first commit.
Security as a property, not a phase.
Controls that apply by default — guardrails and policy as code, so every release ships already compliant.
We keep running what we build.
Deploy, govern and evolve — with published response times and a named lead engineer on every account.
Engineering, security and operations under one roof, so what we build is secure from day one and keeps running at scale.
Every engagement states its scope, its deliverable and the outcome it changes. If we can't name what you'll be holding at the end, we won't sell you the work.
Every engagement starts with the business result you need, and ends with evidence that you got it.
Fewer handoffs. Quicker decisions. Tighter control.
AI agents and automation across finance, HR, IT and customer operations, so routine work runs on its own and your people focus on the decisions that move the business.
Secure by default. Compliant all year round.
Guardrails, policy as code and continuous evidence collection, so SOC 2, ISO 27001 and HIPAA audits stop being an annual scramble.
Understand first. Change in safe steps.
We map legacy systems before we touch them, then modernise in small, reversible releases that your own teams can run and extend.
We work inside your existing cloud, security and data tooling — no rip-and-replace required.
Client names on request under NDA. Every figure came from a report we handed over.
Eleven AWS accounts, no centralised logging, four publicly reachable data stores. Criticals closed in nine days.
Policy-as-code gates and automated ticket routing. Backlog fell from 340 open items to 61 in one quarter.
Nine months of readiness: control mapping, evidence automation and two internal dry runs.
Two counter-turning arcs meeting at a node — the S of Sarsha, and the handoff between the machine and the engineer. The gradient runs through the same teal, blue and violet as the sky above.