Cloud Architecture & Migration
Infrastructure modernization, serverless architecture and multi-cloud strategy built for scale.
- Landing zones
- Serverless refactors
- Multi-cloud strategy
Cloud & AI consultancy · Built on Claude
Production Claude AI agents, on cloud infrastructure built to scale
We build production AI agents on Anthropic's Claude, and design, migrate and operate the cloud infrastructure they run on, delivered by senior architects.
Anthropic ClaudeAWSGoogle CloudMicrosoft AzureKubernetesSnowflakeTerraform
99.9% Uptime | 40% Infrastructure Cost Reduction
Services
Four disciplines, one delivery team
Every engagement combines architecture, applied AI and operational rigor so results survive contact with production.
AI & ML Integration
Claude-powered agents, enterprise LLM deployment and predictive analytics wired into your systems.
- Claude agents & tool use
- Private LLM stacks
- Predictive analytics
DevOps & MLOps Pipeline
CI/CD for AI models, automated scaling and full-stack infrastructure monitoring.
- Model CI/CD
- Autoscaling
- Observability
Cloud Security & Compliance
Data privacy, threat detection and automated governance across every environment.
- Zero-trust
- Threat detection
- Policy as code
Not sure where to start?
A two-week infrastructure and AI-readiness audit gives you a costed roadmap.
Built on Claude
Production agents powered by Anthropic's Claude
Claude is the model behind our client agent work. We design, evaluate and deploy Claude Sonnet and Opus agents inside our clients' own cloud boundaries, then hand over the code, prompts and evals.
- Claude Sonnet & Opus via the Claude API, Amazon Bedrock and Google Vertex AI
- Tool use, multi-step agents and MCP integrations
- Claude Code across our own engineering and delivery
Agentic workflows
Claude tool use and MCP servers that let agents act on ticketing, CRM, data warehouse and cloud APIs, with human approval where it matters.
Retrieval assistants
Claude grounded in private documents with citations, access controls and audit logs, for teams that can't send data to a black box.
Deploy where your data lives
Claude API, Amazon Bedrock or Google Vertex AI, chosen to fit each client's compliance, procurement and data-residency needs.
Evals & cost control
Every agent ships with an evaluation suite, token-cost tracking and model routing between Sonnet and Opus.
Solutions
Selected case studies
Outcomes from recent enterprise engagements across regulated and high-scale environments.
Financial services
Multi-region migration for a 12M-user platform
Replatformed a monolith onto event-driven serverless, cutting p95 latency by 61% and infra spend by 38%.
Healthcare
Private LLM assistant on regulated data
Deployed a retrieval assistant inside a compliant VPC, reducing clinical documentation time by 4.2 hours a week per user.
Logistics
Forecasting pipeline with automated retraining
Built an MLOps pipeline with drift detection that raised route forecast accuracy by 22%.
About
A small team of principal architects
We are cloud and machine-learning engineers who spent a decade inside platform teams at scale. We stay deliberately small, work directly with your engineers, and hand over everything we build.
Senior-only
No layered account teams — the people who scope the work deliver it.
Vendor neutral
We recommend the architecture that fits, not the one we resell.
Knowledge transfer
Documentation, runbooks and pairing are part of every sprint.
Outcome contracts
Engagements are scoped against measurable cost and latency targets.
How we work
From audit to continuous optimization
A four-stage engagement model that de-risks delivery and keeps momentum after go-live.
- 01
Audit & Strategy
We map your infrastructure, spend and data readiness, then agree on measurable outcomes.
- 02
Architecture Design
Reference architecture, cost model and security posture designed before a line of code ships.
- 03
AI Implementation
Pipelines, models and agents delivered in production increments with your engineers alongside.
- 04
Continuous Optimization
Ongoing FinOps, evaluation and reliability engineering to keep gains compounding.
FAQ
Claude agents and cloud consulting, answered
Common questions from teams planning their first production AI agent or cloud migration.
Do you build AI agents on Anthropic's Claude?
Yes. Claude is the model behind our client agent work. We build tool-using agents, MCP integrations and retrieval assistants on Claude Sonnet and Opus, and ship each one with an evaluation suite.
Should we use the Claude API, Amazon Bedrock or Google Vertex AI?
It depends on where your data and contracts already live. Teams on AWS often prefer Bedrock, Google Cloud teams prefer Vertex AI, and the Claude API gets new features first. We recommend one during the audit based on compliance, procurement and data residency.
Will our data be used to train public AI models?
No. We deploy agents inside your own cloud account wherever possible, and client data is never used to train public AI models. Our privacy policy sets out exactly how data is handled.
How does an engagement start?
Most clients start with a two-week infrastructure and AI-readiness audit. You get a costed roadmap covering architecture, model choice and the first agent or migration to ship.
Do you work with companies outside India?
Yes. We are based in India and work remotely with engineering teams worldwide.
What do we own at the end of a project?
Everything we build: code, prompts, evaluation suites, infrastructure as code, runbooks and documentation. Knowledge transfer is part of every sprint.
50%+
Faster AI deployment
35%
Avg. cloud spend saved
24/7
Managed infrastructure
Ready to cut cloud spend and ship AI faster?
Book a 30-minute discovery call. We respond within 24 hours.