Three disciplines sit behind our work: data, AI and security, delivered as six practices. Each is led by a principal architect in the U.S., with certified teams in the U.S. and India.
Cloud & Platform Engineering and Professional Staffing sit underneath all three: the platform the framework runs on, and the people who build it.
Nothing downstream works without it. Governed platforms, pipelines and integration layers so your data is usable by people and reachable by agents.
Agents designed against real workflows, grounded in that data, and wired into the systems where work actually happens. Gemini, OpenAI and Claude.
What makes the first two deployable. Identity, access and AI governance designed in at discovery, so every agent runs inside your controls.
Agents grounded in Workspace and enterprise data, with retrieval that respects existing access controls.
GPT models and agent workflows deployed inside your Microsoft estate or directly against the API.
Claude agents with tool use into your systems of record, for long-context and document-heavy work.
Gemini Enterprise, OpenAI and Claude agents in production within a quarter, inside your governance.
Most enterprise AI stalls between a promising pilot and a system people rely on. We close that gap: pick the use cases that pay, design the agent architecture, ground it in your data, wire it into the systems where work happens, and ship it with evaluation, cost controls and audit trails in place. Then we scale it from one team to the enterprise.
Scope an AI programGoverned data that people and AI agents can both trust.
Agents are only as good as the data they can reach. We modernize warehouses into governed platforms on Snowflake, Databricks and Microsoft Fabric, build the pipelines and semantic layers agents depend on, and put lineage, quality and access controls where they belong: in the platform, not in a slide.
Assess your data platformAgents that act inside your systems, not chatbots that describe them.
Deep enterprise integration experience is what lets our AI work reach ERP, CRM, EHR and plant systems. We replace brittle point-to-point interfaces with API and event layers, expose them as tools agents can call safely, and add the observability that keeps integrations honest.
Review your integration landscapeA platform built for AI workloads, not retrofitted for them.
AI changes what a platform has to do: GPU scheduling, vector stores, model gateways, cost visibility. We build and run landing zones, Kubernetes platforms and DevOps pipelines on Azure and Google Cloud that meet those demands and your security baseline.
Plan your platformAI you can put in front of an auditor.
Security is in the company name, and every practice inherits it. We design identity, access and monitoring for AI-era estates, add prompt, output and data controls to agent deployments, and run security operations that see AI systems as first-class assets.
Request a security reviewSenior capacity without the hiring cycle.
When the work needs people more than a project, we embed certified architects, engineers and data specialists in your team on U.S. hours, backed by delivery centers in Hyderabad, Bangalore and Chennai. Same vetting, same governance, your management.
Describe the role you need
Legacy warehouse migrated to a governed Snowflake platform with rebuilt pipelines, lineage and access controls, the data foundation a later AI program was built on.
Agents integrated into Salesforce so service work is actioned in the system of record rather than summarized beside it, with audit trails on every action.
Client names, figures and quotes are withheld until written permission is on file.
A 45-minute working session with a CSW architect, not a sales deck.
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