We design and deploy multi-agent AI systems that automate complex enterprise workflows end-to-end — driving productivity, compliance, and business outcomes across Financial Services, Public Sector, and Healthcare.
Generic AI tools answer questions. Agentic AI systems pursue goals — planning, executing, and adapting across multi-step enterprise workflows with minimal human intervention.
We deploy crews of specialised agents — each with a defined role, memory, and toolset — coordinated by an orchestrator that decomposes enterprise goals into executable workflows. Built on CrewAI and LangGraph, powered by Claude.
Our agents connect to your existing systems — HRMS, ERP, CRM, regulatory databases, document repositories — via MCP (Model Context Protocol), the universal standard for AI tool integration. No rip-and-replace required.
Every agent carries a cryptographic audit trail. Human-in-the-loop escalation is designed at the architecture level — not bolted on. AI governance frameworks aligned to EU AI Act, UK AI Safety Institute, and SEBI BRSR requirements.
We build agents that understand your industry context — not generic AI wrappers. Regulatory frameworks, domain terminology, compliance logic, and sector-specific data structures are embedded in the agent design, not prompted in.
We define, measure, and report productivity uplift before deployment begins. Every engagement starts with a baseline measurement and a committed outcome — cost reduction, time savings, error rate, or throughput — not a feature list.
Grounded in Philosophy of AI and Sustainability governance principles, our systems are designed to be explainable, auditable, and fair. Every decision can be traced to its source data, reasoning chain, and the human policy that authorised it.
From a high-level enterprise goal to a governed, auditable output — here is what happens inside an agentic AI system we build for your organisation.
A business goal is submitted — "generate our CSRD compliance report for Q2" or "screen all NIFTY500 scrips for Wave 3 Elliott setups." The orchestrator agent decomposes this into a structured task plan with dependencies, data requirements, and agent assignments.
Specialised agents execute simultaneously — Data Retrieval agents pull from connected enterprise systems and APIs, Analysis agents apply domain logic and regulatory frameworks, Compliance agents validate outputs against current rules.
When an agent encounters a data discrepancy, a compliance flag, or a decision that exceeds its confidence threshold, it pauses and routes to the designated human reviewer with full context, source data, and a recommended resolution — not a vague alert.
The Narrative agent assembles the final output in the required format — board report, regulatory filing, API response, dashboard update. Every decision made by every agent is logged with timestamp, source, reasoning, and the human policy that authorised it.
Business outcomes delivered
Agent Architecture — illustrative
Specialised agent crew
Connected tools & systems
Governed output
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Agentic AI only delivers value when it understands your domain as deeply as it understands the technology. Our practice is built on 25 years of enterprise leadership across these sectors.
Automate complex financial workflows while maintaining regulatory compliance, audit readiness, and human accountability at every decision point.
Transform public service delivery through agentic systems that process at scale, maintain equitable governance, and preserve citizen trust through transparency.
Deploy agentic AI in healthcare workflows where accuracy, safety, and regulatory compliance are non-negotiable — augmenting clinical teams, never replacing human judgment.
Accountability, escalation paths, and sign-off authority are defined before a single line of code is written.
Every agent decision is explainable in regulatory language — not technical jargon. Audit-ready by design.
We define precisely which decisions require human sign-off. Autonomy is earned, not assumed.
EU AI Act, UK AI Safety Institute, UAE AI governance, SEBI — our systems adapt as frameworks evolve.
Enterprise AI fails when it starts with technology. We start with your business problem, your governance requirements, and your definition of success.
A paid, structured 2-day engagement where we map your highest-value automation opportunity, define measurable success criteria, and identify governance requirements. Deliverable: a signed problem statement and ROI model.
2 days · ₹1–2 lakhsA working, deployed agentic system on one well-defined workflow. Real data, real integrations, real outputs. Measured against the baseline established in Discovery. No slides — a live demonstration.
4–8 weeks · ₹5–15 lakhsFull deployment with security hardening, enterprise SSO integration, monitoring, audit logging, and staff enablement. Includes governance documentation and regulatory compliance sign-off where required.
3–6 months · ₹25–75 lakhsQuarterly capability reviews, regulatory update incorporation, agent performance monitoring, and expansion to new workflows as your AI maturity grows.
Monthly retainer · ₹2–5 lakhs/moA paid discovery is a signal of seriousness — from both sides. It ensures we understand your problem deeply enough to commit to an outcome.
Any engineer can deploy Claude. We bring 25 years of enterprise leadership in Financial Services, Public Sector, and Sustainability — embedded in how we design agent logic.
We commit to a measurable business outcome before deployment begins. If the agent does not deliver the agreed outcome, we stay until it does.
For regulated industries, AI governance is a regulatory requirement, not a nice-to-have. We will not deploy agents in production without a documented governance framework.
Headquartered in Mumbai. Serving enterprise clients in India, the United Kingdom, and the Gulf — remotely and via quarterly in-market visits.
We are an Anthropic Claude Partner — the most advanced reasoning model available — combined with open-source orchestration frameworks and enterprise integration standards.
AI Model Layer
Claude Sonnet 4 — best-in-class reasoning, 200K context, MCP-native, built for enterprise governance and safety. Certified Anthropic Claude Partner.
Orchestration
Multi-agent workflows with CrewAI for rapid deployment. LangGraph for stateful, long-running enterprise agents with full checkpoint and recovery.
Integration Standard
Model Context Protocol — Anthropic's open standard for universal tool integration. One interface connects agents to any enterprise system without custom connectors.
Observability
Full observability, performance monitoring, and audit trail for every agent decision. Regulatory-grade logging for financial and public sector deployments.
Deployment
AWS, Azure, GCP, or private cloud. On-premise for data-sensitive deployments in regulated industries. Your data never leaves your environment.
Data & Analytics
yfinance, pandas, pandas-ta for financial data. HRMS, ERP, and regulatory database connectors. Real-time WebSocket feeds for market monitoring agents.
Security
SSO, RBAC, encryption at rest and in transit. SOC 2 aligned architecture. Data residency controls for UK GDPR and India DPDPA compliance.
Standards
Agent governance frameworks aligned to EU AI Act, UK AI Safety Institute guidelines, UAE AI governance, and SEBI BRSR reporting requirements.
We begin every engagement with a no-obligation 45-minute conversation — to understand your highest-value automation opportunity and whether agentic AI is the right solution. No slides. No generic demos. A real conversation about your specific problem.