Running Semantic Kernel or AutoGen in production?Plan your move to Microsoft Agent Framework

AI Agent Development for the Enterprise

Agents that look things up, act in your systems and hand over to a person when they should. We build them mainly with Microsoft Agent Framework, run them on Microsoft Foundry, other Azure services or your own servers, and test each one in a small pilot before production.

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Agent, chatbot or workflow?

Not every AI project needs an agent. The three approaches differ in how much the software decides for itself.

Chatbots, workflows and agents compared
ApproachWhat it doesWhen it fits
ChatbotAnswers questions in a conversation, from content you choose. It does not change anything in your systems.People need answers rather than actions: support questions, policies, product information. See our AI chatbot development.
WorkflowRuns steps you define, along a path set in code. A language model may handle a step, such as reading a document, but it does not choose the path.The process is known and must run the same way every time, with a clear audit trail: approvals, onboarding, document intake.
AgentWorks towards a goal. It decides which steps to take, calls tools to act in your systems and checks the results, within limits you set.The path changes from case to case and needs judgement: resolving support cases, chasing missing information, triaging requests.

Many systems combine them: a workflow fixes the order and the approval points, and agents handle the steps that need judgement. Microsoft Agent Framework supports both. If a chatbot or a plain workflow will do the job, we will tell you, because both are simpler to test and usually cheaper to run.

Agents we build

Support case resolution

An agent reads the request, looks up the order or account, applies your policy and either resolves the case or passes it to your team with the facts gathered. Refunds and exceptions wait for approval.

Operations and back-office work

An agent reconciles records between systems, checks documents against your rules and updates your ERP or CRM, logging every change for review.

Knowledge agents

An agent answers questions from your documents and data, shows where each answer came from and can act on what it finds, for example by raising a request. We build the retrieval behind it as part of our custom AI solutions.

Helpdesk in Microsoft Teams

An IT or HR helpdesk that staff use inside Teams. It answers policy questions, handles routine requests within its permissions and raises tickets for the rest. See our Teams and Microsoft 365 Copilot agents.

Multi-step workflows

We build processes such as intake, review and approval on Microsoft Agent Framework, with several agents sharing the work. Agent Framework workflows can save their state, so long-running work can resume after an interruption.

Choosing the stack

We build mainly on Microsoft’s stack. The options below can be combined.

Agent frameworks and services we choose between, as of October 2026
OptionWhat it isUse it when
Microsoft Agent FrameworkMicrosoft’s open-source (MIT) framework for agents and multi-agent workflows in .NET and Python, generally available since April 2026. Microsoft describes it as the direct successor to Semantic Kernel and AutoGen.You want agents in your own code, with full control over models, tools and hosting. We recommend it for most new agent work.
Foundry Agent ServiceMicrosoft’s managed platform for building, deploying and scaling agents. Its hosted agents, generally available since July 2026, run your own agent code with a managed endpoint, automatic scaling and a Microsoft Entra agent identity.You are on Azure and want Microsoft to run the agent infrastructure. Agent Framework code can run there as a hosted agent, though Agent Framework’s hosting packages are still prerelease.
Microsoft 365 Agents SDKMicrosoft’s generally available SDK for conversational agents in C#, JavaScript and Python. Microsoft positions it for multichannel agents: one agent for Teams, Microsoft 365 Copilot, websites and other apps.The agent must reach people beyond Teams and Microsoft 365 Copilot. Agent Framework can supply the AI logic inside it. For agents built specifically for Teams, Microsoft positions Teams SDK, which also reaches Microsoft 365 Copilot.
Copilot StudioMicrosoft’s graphical, low-code studio for building and managing agents and publishing them to channels such as Teams and websites.Your own team wants to build and change the agent without heavy development work, and its features cover the process. We then recommend it over custom code.
LangChainA framework for language-model applications: retrieval over documents, tool calling and multi-step chains.Your team works in Python and already has LangChain code. We build on it rather than start again.

Guardrails we build in

An agent that can act needs limits that do not depend on the model getting things right. We build these in from the pilot onwards.

  • Least-privilege tools: each tool reaches only the data and actions its task needs, under an identity you control and can revoke. On Foundry Agent Service, each hosted agent gets its own Microsoft Entra agent identity when it is deployed.
  • Approval for sensitive actions: payments, refunds, deletions and messages to customers wait for a person to approve them. Microsoft Agent Framework workflows can pause for that decision and continue once it is made.
  • Input and output checks: we check requests before they reach the model, tool calls before they run and replies before they are sent, using Agent Framework middleware. On Microsoft Foundry we add its guardrails, which are generally available for models sold by Azure and in preview for agents.
  • Tracing of every action: each model call and tool call is traced with OpenTelemetry, which is built into Agent Framework, so any answer or action can be followed back to its cause.
  • An evaluation set run before each release: real cases with agreed expected outcomes, run again whenever a prompt, model or tool changes.
  • Handover to people: when the agent is unsure, out of its scope or asked for a person, it passes the case to your team with everything gathered so far.

From pilot to production

  1. Discovery call

    We look at the process, the systems it touches and what a good result would be, and tell you plainly whether an agent is the right answer. To begin, book a free discovery call (opens in a new tab).

  2. Scope the pilot

    We pick one process with you and agree the tools the agent may use, the actions that need approval and the success criteria. Scope, timeline and price go into a statement of work.

  3. Build and test the pilot

    We build the agent against test versions of your systems, run the evaluation set and put it in front of a small group of your staff. You see the traces, not only a demo.

  4. Move to production

    If the pilot meets its success criteria, we prepare it for wider use: permissions reviewed, monitoring and alerts in place, and a staged rollout.

  5. Hand over and support

    You receive the code, prompts, evaluation set and documentation. We support and improve the agent as needed or on a monthly retainer, Monday to Friday, 9 AM to 6 PM IST.

Consulting
From ₹2,500 (US$40) an hour
Monthly retainer
From ₹2,00,000 (US$4,000) a month
Pilots and fixed-scope projects
Quoted per statement of work

GST is added to Indian invoices. Rate cards by business size and add-ons are on our pricing page.

Sources

Last reviewed by Jagdish Kumawat, Founder & Director

Frequently Asked Questions

What is an AI agent?

An AI agent is software that uses a language model to work towards a goal: it decides which steps to take, calls tools such as your APIs and databases to carry them out, and checks the results.

How is an agent different from a chatbot?

A chatbot answers questions from content you give it. An agent can also act: it looks up records, raises tickets or updates bookings in your systems through tools, and asks a person before anything sensitive.

Which framework do you use?

Usually Microsoft Agent Framework, in C# or Python. Microsoft describes it as the direct successor to Semantic Kernel and AutoGen. Where they fit better, we use Foundry Agent Service, the Microsoft 365 Agents SDK, Copilot Studio or LangChain.

How do you stop an agent doing the wrong thing?

We limit what it can do and check what it does. Each tool has only the access its task needs, sensitive actions wait for a person’s approval, inputs and outputs are checked, every action is traced, and an agreed evaluation set runs before each release.

How long does a pilot take?

It depends on the process and the systems involved, so scope and timeline are agreed in the statement of work before we start. We keep the pilot deliberately small: one process, a few tools and clear success criteria.

Where does our data stay?

Where we agree it should: in your own Azure subscription, including Microsoft Foundry, or on your own servers. The agent sends data only to the model service and systems you approve, and if data must stay in one region, we first check which services are offered there.

Should we use Copilot Studio instead of custom code?

Sometimes, yes. Copilot Studio is Microsoft’s low-code option for building agents without heavy development work, and if it covers your process we will recommend it. We build agents in code when you need full control over models and orchestration.

What does an AI agent project cost?

Consulting starts at ₹2,500 (US$40) an hour and monthly retainers at ₹2,00,000 (US$4,000); pilots and fixed-scope projects are quoted per statement of work after a free discovery call.

Related services

Free discovery call

Tell us what your agent should do

We'll tell you the simplest approach that will work — Microsoft Agent Framework, Copilot Studio or no agent at all — and what a pilot would involve.

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