Agentic AI

Agentic AI Development Company in India

Indian GCCs and enterprises are moving past AI pilots to agents that do real work. Opsio's India team builds agentic AI systems that survive production — governed tool use, retrieval, and human-in-the-loop controls — deployed on AWS Mumbai or Azure India and operated from Bangalore, DPDP-aligned.

Book a Scoping Call See What's Included

Trusted by 100+ organisations across 6 countries

6-8 wk

Scoped POC to production pilot

AWS Mumbai

& Azure India regions

50+

AI & cloud engineers

DPDP

-aligned delivery

Claude Agent SDK

Amazon Bedrock

Azure OpenAI

AWS

Model Context Protocol

ISO 27001 Certified

Delivered by Opsio

What's Included

End-to-end agentic AI engineering — from the first scoping workshop to a monitored production system.

Agent Architecture & Tool Design

We design the agent's tool surface, permissions, and control flow — what it can call, what needs approval, and how it recovers from errors. Single-agent or multi-agent orchestration depending on the task, built for auditability rather than a flashy demo.

Claude Agent SDK & MCP Integration

Production agents on the Claude Agent SDK with Model Context Protocol servers connecting your data, APIs, and internal tools through a governed, reusable interface — so agents act on your systems without hard-coded, ungoverned access.

Retrieval & Grounding (RAG)

Retrieval pipelines that ground agents in your documents and data with the right chunking, embeddings, and re-ranking — so answers and actions are based on your reality, not the model's training data.

Evaluation & Guardrails

An evaluation harness that scores the agent on your real tasks before and after every change, plus guardrails and human-in-the-loop gates on irreversible actions. You ship on evidence, not vibes.

Deployment & Observability

Deployment on your cloud (AWS, Azure, GCP) with full tracing of every agent decision, tool call, and cost — dashboards and alerts so you can see what the agent did and what it spent.

Operate & Improve

We run the system post-launch: monitoring, evaluation on live traffic, prompt and tool iteration, model upgrades, and token-cost optimization — continuous improvement, not a hand-off.

Verified customer

Opsio has been a reliable partner in managing our cloud infrastructure. Their expertise gives us the confidence to focus on our core business while knowing our environment is in good hands.

Magnus Norman

Head of IT · Löfbergs

Agentic AI development in brief

Agentic AI development builds systems that act autonomously — planning, calling tools, retrieving data, and completing multi-step tasks — rather than answering one prompt at a time. The value lies in that autonomy; the difficulty lies in making it reliable, safe, and observable in production. Opsio engineers agentic systems end to end on the Claude Agent SDK and Model Context Protocol, deployed on AWS, Azure, or Google Cloud, with tool-permission design, retrieval grounding, evaluation harnesses, guardrails, human-in-the-loop gates, and full tracing — then operates them post-launch with monitoring, evaluation on live traffic, and cost control. Delivered by 50-plus certified engineers under ISO 27001 from Opsio's Bangalore centre, agentic AI development takes a promising prototype to a governed system the business can depend on.

From AI pilot to an agent that ships

Agentic AI is the step beyond a chatbot: an agent plans, calls tools, reads and writes data, and completes a multi-step task on its own. That autonomy is where the value is — and where most Indian AI programmes stall, stuck in a pilot that impresses in a demo but never reaches production. Opsio's India team closes that gap, engineering agents that act reliably against your systems, stay within guardrails, and recover from failure. We build on what reaches production for Indian teams: Claude and the Claude Agent SDK for autonomous coding and tool use, the Model Context Protocol (MCP) to connect agents to your data through a governed interface, and AWS Bedrock or Azure OpenAI where cloud and compliance posture require it. For GCCs and regulated enterprises, we deploy in AWS Mumbai or Azure India regions and align with the Digital Personal Data Protection (DPDP) Act so data-residency and governance are handled from the start.

The hard parts are rarely the model call — they are tool permissions, retrieval grounding, an evaluation harness, observability, and human-in-the-loop gates on irreversible actions. We engineer all of it and hand you a system with tests, dashboards, and runbooks, then operate it: monitoring, evaluation on live traffic, iteration, and token-cost control in rupee-aware budgets. You get an agent that keeps working and a Bangalore team accountable for it. Featured reading from our knowledge base: Agentic AI in Digital Transformation: India Use Cases, How We Help Businesses Succeed with AI/ML Development, and Which company is best for cyber security in India?. Related Opsio services: IoT Solution Development India, AI Chatbot Development for India, AI Security & Compliance India, and IoT Predictive Maintenance for India.

Agent Architecture & Tool DesignAgentic AI

Claude Agent SDK & MCP IntegrationAgentic AI

Retrieval & Grounding (RAG)Agentic AI

Evaluation & GuardrailsAgentic AI

Deployment & ObservabilityAgentic AI

Operate & ImproveAgentic AI

Claude Agent SDKAgentic AI

Amazon BedrockAgentic AI

Azure OpenAIAgentic AI

Agent Architecture & Tool DesignAgentic AI

Claude Agent SDK & MCP IntegrationAgentic AI

Retrieval & Grounding (RAG)Agentic AI

Evaluation & GuardrailsAgentic AI

Deployment & ObservabilityAgentic AI

Operate & ImproveAgentic AI

Claude Agent SDKAgentic AI

Amazon BedrockAgentic AI

Azure OpenAIAgentic AI

How Opsio Compares

Capability	DIY / In-house	Generic AI Vendor	Opsio Agentic AI
Time to production pilot	9-18 months	Fast but shallow	6-8 weeks
Tool permissions & guardrails	Your team	Limited	Designed in
Evaluation harness	Rarely built	Vendor-defined	On your real tasks
Observability & audit trail	Your team	Basic	Full tracing
Model flexibility	Whatever you know	Locked to vendor	Claude / Bedrock / Azure
Operated after launch	Your team	Support only	Fully managed

Ready to get started?

Book a Scoping Call

What You Get

Scoped agentic use-case design with success criteria and feasibility assessment

Working agent built on the Claude Agent SDK with governed tool use

Model Context Protocol (MCP) integration to your data and systems

Retrieval-augmented grounding pipeline

Evaluation harness scoring accuracy and safety on your real tasks

Guardrails and human-in-the-loop gates on irreversible actions

Deployment on your cloud with full decision and cost tracing

Dashboards, alerts, and operator runbooks

Managed operation with evaluation on live traffic and cost optimization

Pricing & Investment Tiers

Transparent pricing. No hidden fees. Scope-based quotes.

Scoping & Feasibility

$10,000-$25,000

1-2 week engagement

Why Choose Opsio for Cloud Services

Why enterprises choose Opsio to build agentic AI.

Production-first, not demo-first

We build for the failure modes that break agents in production — permissions, recovery, evaluation, cost — from day one.

Claude & MCP specialists

Deep Claude Agent SDK and Model Context Protocol expertise, backed by a live library of Claude Code and agentic engineering knowledge.

India-region deployment

AWS Mumbai and Azure India deployment with DPDP-aligned data residency and governance for GCCs and regulated enterprises.

Governed by design

Guardrails, human-in-the-loop gates, and full audit trails so legal, risk, and security can sign off.

We operate what we build

Monitoring, evaluation on live traffic, and cost control keep the agent working after launch.

Bangalore delivery, ISO 27001

Certified, secure delivery from 50+ AI and cloud engineers based in Bangalore.

Not sure yet? Start with a pilot.

Begin with a focused 2-week assessment. See real results before committing to a full engagement. If you proceed, the pilot cost is credited toward your project.

Start a Pilot

Our 4-Phase Delivery Process

A staged path from idea to a running, governed agent.

Scope & Feasibility

A workshop to pick the highest-value agentic use case, assess data and tool readiness, and define success criteria. Deliverable: a scoped design and feasibility report. Timeline: 1-2 weeks.

Prototype & Evaluate

Build a working agent against real tasks with an evaluation harness that measures accuracy, safety, and cost. Deliverable: an evaluated prototype with documented metrics. Timeline: 2-3 weeks.

Harden & Deploy

Add guardrails, human-in-the-loop gates, retrieval, tracing, and CI, then deploy on your cloud. Deliverable: a production pilot with dashboards and runbooks. Timeline: 2-3 weeks.

Operate & Improve

Run the agent with monitoring, evaluation on live traffic, iteration, and cost optimization. Timeline: ongoing.

Key Takeaways

Agent Architecture & Tool Design
Claude Agent SDK & MCP Integration
Retrieval & Grounding (RAG)
Evaluation & Guardrails
Deployment & Observability

Industries Served by Opsio

Agentic AI applied where the workflow is genuinely multi-step.

GCCs & Captives

Agentic automation for global capability centres — coding, operations, and reporting agents with governance.

Software & DevOps

Coding agents, automated code review, and CI/CD agents on the Claude Agent SDK.

BFSI

Governed agents for research, reconciliation, and reporting with audit trails and DPDP alignment.

Customer Operations

Agents that resolve multi-step service tasks end to end, not just answer FAQs.

Agentic AI Development Company in India — FAQ

What is agentic AI development?

Agentic AI development is the engineering of AI systems that act autonomously to complete multi-step tasks — planning, calling tools, retrieving data, and taking actions — rather than just answering a single prompt. In practice it involves designing the agent's tool surface and permissions, grounding it in your data via retrieval, building an evaluation harness to verify it works, adding guardrails and human-in-the-loop controls for safety, and deploying it with full observability. Opsio delivers all of this end to end and then operates the system in production.

How is an AI agent different from a chatbot?

A chatbot responds to one message at a time and typically only produces text. An AI agent pursues a goal: it decides what steps to take, calls tools and APIs, reads and writes data, checks its own progress, and completes a task with limited human input. That autonomy delivers far more value but requires real engineering around permissions, error recovery, evaluation, and governance — which is exactly what agentic AI development provides.

Which models and frameworks do you build on?

We are model-pragmatic. For autonomous coding and tool use we build on Claude and the Claude Agent SDK; we use the Model Context Protocol (MCP) to connect agents to your data and services through a governed interface; and we deploy on AWS Bedrock or Azure OpenAI where your cloud and compliance requirements call for it. We select the architecture that meets your accuracy, latency, and cost targets rather than committing to one vendor's stack.

How long does it take to build a production agent?

A typical path from scoping to a production pilot runs 6-8 weeks: 1-2 weeks of scoping and feasibility, 2-3 weeks to build and evaluate a prototype, and 2-3 weeks to harden, add guardrails, and deploy. Timelines depend on how many systems the agent must integrate with and how strict the governance requirements are. We front-load evaluation so you know whether the agent works before committing to full deployment.

How do you keep autonomous agents safe?

Safety is designed in, not bolted on. We scope each tool's permissions so an agent can only do what it should, gate irreversible or high-risk actions behind human approval, ground the agent in your data with retrieval to reduce hallucination, and run an evaluation harness that scores safety and accuracy on your real tasks before and after every change. Every agent decision and tool call is traced, giving you a full audit trail for legal, risk, and security review.

Do you operate the agent after launch, or just build it?

Both — and operating it is where agentic systems succeed or fail. Models, data, and usage patterns change, so an agent that worked at launch drifts without maintenance. Opsio offers managed operation: monitoring, evaluation on live traffic, prompt and tool iteration, model upgrades, and token-cost optimization. You get a system that keeps working and a team accountable for it, not a prototype left to decay.

What does agentic AI development cost?

A scoping and feasibility engagement confirms the use case, design, and expected value; a build-to-production-pilot engagement follows, with ongoing managed operation monthly. Exact pricing depends on integration and governance complexity and is quoted for Indian budgets. Most GCCs and enterprises start with the scoping engagement so the investment decision is evidence-based. Deployment in AWS Mumbai or Azure India keeps data in-region for DPDP compliance.

Can you work with our existing cloud and data?

Yes. We build on your existing AWS, Azure, or Google Cloud estate — deploying in AWS Mumbai or Azure India regions where data residency matters — and connect agents to your data through governed MCP and API interfaces. During scoping we assess data readiness, integration surface, and DPDP obligations so the agent works within your environment and compliance boundaries from the start.

Still have questions? Our team is ready to help.

Book a Scoping Call

Editorial standards: Written by certified cloud practitioners. Peer-reviewed by our engineering team. Updated quarterly.