AI development now extends far beyond building a chatbot or training a model. Enterprises need partners that can connect models to business data, integrate applications, enforce security controls and operate AI reliably after launch. For buyers in India, the right shortlist should compare delivery depth, cloud capability, governance and evidence, not just company size.
This guide examines five top AI development companies with offerings relevant to Indian enterprises: Rapyder, EPAM, Globant, Infosys and Tech Mahindra. It also explains what to ask about AI coding assistants and AI tools for software development before you sign.
Which top AI development companies should enterprises in India evaluate?
Rapyder, EPAM, Globant, Infosys and Tech Mahindra each document AI development offerings relevant to enterprises in India. Choose by the work you need built, such as custom GenAI applications, agent platforms or AI-assisted engineering, and compare the proposed team, evidence, security controls and ownership after launch rather than company size.
What "AI development" means in 2026
The phrase covers three different kinds of work, and a company can be strong at one and ordinary at another:
- Building AI products. Designing and delivering custom machine learning, GenAI and agent applications, including the data pipelines and operations around them.
- Using AI to build software. Applying AI coding assistants and other AI tools for software development to ordinary engineering work.
- AI-native delivery models. Platforms where AI agents do much of the work under human supervision, often priced by output instead of hours.
AI coding assistants suggest, generate, explain and review code inside developers’ tools. AI tools for software development is the wider category: test generation, code review, documentation, security scanning, migration helpers and agents that work from requirements to code. Two of the five companies below document tools aimed at software delivery itself: Infosys, through its Amazon Q Developer collaboration, and Globant, through Globant CODA.
Top 5 AI development companies in India to compare
| Company | Documented evidence | AI development focus | Question for the proposed team |
|---|---|---|---|
| Rapyder | Custom GenAI services and published AWS implementations | Defined GenAI applications connected to cloud and data engineering | Who owns quality and operations after launch? |
| EPAM | DIAL orchestration platform | Open-source GenAI orchestration across models and applications | Who operates DIAL, and what support do we get? |
| Globant | AI Pods (June 2025) and Glob.AI (August 2026) | AI-agent service units supervised by experts, including software delivery | What do agents do, and what do people review? |
| Infosys | Topaz and Amazon Q Developer collaboration with AWS (January 2026) | AI across enterprise software delivery and customer applications | Which Topaz components and developer tools are included? |
| Tech Mahindra | TechM Orion announcement (July 2025) | AI agent development and deployment platform | Which orchestration components and permitted actions are included? |
The focus column is an editorial reading of the evidence, not a finding that one company performs better than another.
Rapyder
- Documented scope: Custom GenAI application development connected to AWS cloud engineering, data integration and deployment. Rapyder is an AWS Premier Tier Services Partner with the AWS Generative AI Competency, now the AWS AI Competency.
- Evidence: Rapyder’s generative AI development services and the AWS Partner Network article on its Call Agent Analyzer, which analyzes human customer-service calls.
- Consider when: you have a defined business workflow and want its application, data connections and AWS operating environment delivered together.
- Verify before selection: the architecture, an evaluation set, delivery milestones, knowledge transfer and who supports the application after launch.
EPAM
- Documented scope: EPAM launched its DIAL orchestration platform on 1 August 2023 and released an open-source version under the Apache 2.0 license in December 2023. DIAL 3.0, released on 24 June 2025, adds support for agentic workflows and data-native reasoning.
- Evidence: the DIAL launch, the open-source release and the DIAL 3.0 announcement.
- Consider when: you want an open-source orchestration layer for several models and applications, delivered by an engineering-led partner.
- Verify before selection: license obligations, who runs the platform after handover, support terms and how it fits your cloud environment.
Globant
- Documented scope: Globant announced AI Pods on 5 June 2025 and describes them as the first subscription model for AI-powered engineering. They are powered by Globant Enterprise AI, and the agent lineup includes Globant CODA, which covers code generation, testing and deployment across the software development lifecycle. On 6 August 2026, Globant introduced Glob.AI, a platform for buying AI Pods with pricing linked to output or consumption.
- Evidence: the AI Pods announcement and the Glob.AI announcement.
- Consider when: you want continuous, subscription-style delivery in which AI agents do much of the work and experts supervise it.
- Verify before selection: what the agents do and what people review, the pricing unit, who owns the outputs and how supervision is recorded.
Infosys
- Documented scope: On 7 January 2026, Infosys announced an AWS collaboration that combines Infosys Topaz with Amazon Q Developer for software development, alongside Amazon Bedrock for customer engagement applications.
- Evidence: Infosys and AWS collaboration.
- Consider when: you are transforming engineering across a large enterprise estate on AWS.
- Verify before selection: which Topaz components and developer tools apply, code and IP ownership, and the security controls around AI-assisted changes.
Tech Mahindra
- Documented scope: TechM Orion is a platform for developing and deploying AI agents, announced on 24 July 2025 and powered by NVIDIA accelerated computing.
- Evidence: Tech Mahindra’s TechM Orion announcement.
- Consider when: you need agent development integrated with established enterprise systems, with defined limits on tool use and business actions.
- Verify before selection: current availability, supported integrations, deployment requirements and how actions, approvals and recovery are tested.
What to ask about AI coding assistants and AI tools for software development
If a partner uses AI to write or change your code, you are also buying its habits. Ask:
- Which assistants and models are used on our code, and can we approve or restrict them?
- Where do our code and context go? Ask about processing location, retention and whether anything is used to train models.
- Who reviews AI-generated code, and what tests and security scans must it pass before it merges?
- How are license and IP risks handled, and what do the contract terms say about ownership and indemnity?
- Can we see an audit trail of which changes were AI-assisted?
- How will the effect on delivery be measured, and against which baseline? Cycle time, defect rate and rework on your own project say more than a general claim. For a wider look at the controls, see Rapyder’s guide to AI governance best practices.
How to compare proposals from top AI development companies
- Evidence: a named reference with similar data, integrations and constraints, with the metric and baseline stated.
- Security and data handling: where code and data go, what is retained and who can see it.
- Testing: the evaluation set or test plan, and the acceptance criteria agreed before development.
- Ownership and portability: who owns the code, prompts and configuration, and what happens if you leave.
- Commercial model: whether you pay for effort, subscription or output, and what is included in each.
Separate the pilot from the production commitment, with a decision point where evidence decides whether to continue. For related comparisons, see Rapyder’s guides to the top AI consulting companies in India, the top AWS GenAI partners in India and the best generative AI tools for business.
Start with a reviewable brief
Write a short brief that covers the task, users, data sources, integrations, constraints and intended outcome. Send the same brief to each of the top AI development companies on your shortlist and ask for a written response against the same criteria. The first useful result is a clearer project and a list of what to test before a wider commitment.
Evaluating AI development partners for your next project?
Bring one use case, its data, integrations and acceptance criteria to a scoping conversation.
Frequently Asked Questions
The top AI development companies in India evaluated in this guide are Rapyder, EPAM, Globant, Infosys and Tech Mahindra. Each has a publicly documented AI development offering relevant to Indian enterprises. Buyers should compare project fit, evidence, cloud capability and the proposed delivery team.
Top AI development companies build and operate applications, integrations and supporting data pipelines, while AI consulting companies may focus more heavily on use cases, feasibility and governance. Many providers do both. The statement of work should separate consulting and development deliverables and give each clear acceptance criteria.
Yes. Top AI development companies may use AI coding assistants to suggest, generate, explain and review code inside developers’ environments. People remain accountable for what ships, so every AI-assisted change should still pass human review, testing and security checks.
Yes, if they are configured and governed correctly. Top AI development companies should disclose which tools process your code, where the context goes, what is retained and whether it is used for model training. Confirm the contract, retention settings, access controls, human review and testing before work begins.
Buyers evaluating top AI development companies should ask for named references involving similar data, integrations and constraints, with each result tied to a baseline. Check dated announcements and partner credentials at the source. Then run a paid pilot on your own workflow before making a wider commitment.
Pricing from top AI development companies depends on the scope, data preparation, integrations, evaluation, deployment and support required. There is no useful universal price without those details. Ask for itemized costs and workload assumptions, and compare what each proposal includes before comparing totals.
No. Top AI development companies should treat faster delivery as a measurable hypothesis rather than a guaranteed outcome. Code generation can add review and testing work, and results depend on the task, codebase and process. Measure cycle time, defects and rework against a baseline.
