Build an AI agent for your business or product.
Build AI agents that can understand instructions, use tools, interact with APIs and complete multi-step tasks instead of simply generating text.
- 5+ yearsProfessional experience
- 40k+Users across shipped projects
- DirectDeveloper communication
5+ yrs
building AI agents
Earned through freelance work
Active users across projects
GitHub contributions
Professional experience
Production apps shipped & maintained
Agent types
What can AI agents do?
An agent is a fundamentally different system from a chatbot, even though both often sit behind the same text or voice interface. A chatbot takes an input and returns one response; an agent combines an AI model with tools, memory, retrieval and application logic so it can decide what actions are actually needed, call the right tool or API for each one, look at the result, and decide what to do next — a real decision loop instead of a single request-response pair. That loop is what lets an agent research across multiple sources, update a CRM record, or process a document end to end without a person driving every step. Not every project needs that: if a well-designed prompt or a basic RAG lookup solves the actual problem, building a full agent adds complexity without adding value. If you're weighing an agent against a smaller build, I can help you figure out the right scope when you reach out about your project.
Research Agents
Search, collect and cross-reference information from multiple sources automatically, then summarize findings into a structured brief instead of a pile of raw results you still have to read.
Customer Support Agents
Understand what a customer is actually asking, retrieve the relevant answer from your knowledge base or documentation, and escalate to a human the moment the question falls outside what it knows.
Sales Agents
Qualify inbound leads against your criteria, update CRM records automatically, and trigger the right sales workflow — follow-up, notification, handoff — without a rep touching every new lead manually.
Data Agents
Translate a plain-language question into a database query, run it, and return the insight — without someone writing SQL or building a new dashboard for every new question.
Document Agents
Read contracts, invoices or reports, extract the specific fields or clauses that matter, and route the result into your existing workflow instead of a person doing it by hand.
Workflow Agents
Chain calls across multiple APIs and internal systems, making a decision at each step, to automate a business process that used to require someone stitching the tools together manually.
Features
AI agent features
Tool calling, multi-step workflows and human-approval gates are what separate an agent from basic automation. If the work is really about the application around the agent — auth, dashboards, data layer — that's covered by custom web development too.
Tool Calling
The mechanism that turns a language model into an agent: the model decides which function to call and with what arguments, your application executes it, and the result feeds the next decision.
RAG
Give the agent retrieval access to your private documents and knowledge base via embeddings and a vector database, so its decisions are grounded in your actual data, not general knowledge.
Memory
Carry relevant context across steps and, where the task calls for it, across separate sessions — without stuffing the entire conversation history into every single prompt.
Multi-Step Workflows
Break a complex task into a sequence of smaller actions, execute them one at a time, and adjust the plan based on what each step actually returns.
Human Approval
Pause and require human confirmation before anything sensitive or irreversible — sending an email, issuing a refund, modifying a record — so autonomy doesn't mean unchecked.
Monitoring
Log every action, tool call and failure the agent makes, so when something goes wrong in production you can see exactly what it did and why, not just that it failed.
Let's build your AI agent.
Tell me what you're building. If your agent requires a custom web application layout with dashboards, see my web application development service or learn about hiring an AI developer for custom backend tasks.
Tech Stack
AI agent tech stack
Gemini and OpenAI provide the reasoning and function-calling layer that decides which tool to invoke and with what arguments; task planning, multi-step workflow logic and memory turn that single decision into a completed job; and RAG with vector databases gives the agent grounded knowledge to reason over instead of guessing. The application layer around it — REST APIs, webhooks and OAuth for third-party integrations, deployed on Docker, AWS or Vercel with PostgreSQL and Redis — is what lets the agent actually take actions in the systems you already use.
AI Models
4 core tools
Agent Framework
4 core tools
Knowledge
4 core tools
Application
4 core tools
Integration
4 core tools
Infrastructure
5 core tools
Selected work
Complete digital products, not just websites
SaaS platforms, AI systems, mobile apps, automation pipelines and business management platforms — designed, built and shipped for real clients.
Swasthify — Healthcare Management Platform
A complete healthcare ecosystem connecting doctors, laboratories, patients and administrators through a unified digital platform for healthcare management, reports, analytics and patient services.
Web platform + Android application supporting 10k+ users across projects.
AI
AI Voice Interview Platform — Real-time Voice Assessment
The closest thing in this portfolio to an agent's decision loop: this real-time voice interview platform doesn't just generate one response — it listens to a spoken answer, evaluates it with Gemini against assessment criteria, and decides what to ask next, all through Vapi's real-time voice pipeline with ChromaDB behind it for retrieval. That's the same perceive-evaluate-act pattern agents run on, applied to live conversation instead of text.
AI
AI Video Ads Generator — Automated Content Creation
An AI-powered platform that helps generate promotional video advertisements through an automated content creation workflow.
Donation / NGO
Bring Smile — Donation Platform
A modern donation website designed to help organizations collect donations, communicate their mission and create a simple digital fundraising experience.
Donation / NGO
Plan to Empower — Donation Platform
A purpose-driven donation platform focused on connecting supporters with meaningful social initiatives through a clean and accessible digital experience.
Finance
Legal257 — Finance & Loan CMS
A finance and loan management platform designed to simplify financial service operations, content management and customer workflows.
Donation / NGO
Jonojivan — Donation Platform
A donation-focused digital platform built to support social initiatives, manage campaigns and provide an accessible contribution experience.
E-commerce
Jonojivan — E-commerce Platform
An e-commerce platform designed to manage products, customers, orders and online commerce workflows.
E-commerce
Cleanveda — E-commerce Platform
A complete e-commerce experience with product discovery, shopping workflows, order management and a powerful administrative backend.
AI Blog Automation Platform
Multi-worker AI automation system
A genuine multi-step, multi-worker workflow rather than a single prompt: separate Research, Planning, Outline and Writing workers hand a task off to each other through a BullMQ/Redis queue, with retry logic and an AI quality-evaluation step gating what actually gets published. It's the same tool-calling, multi-step orchestration pattern an agent runs — just applied to content production instead of business operations.
Factory Management Platform
Manufacturing ERP
A complete manufacturing management platform for managing factory operations, workforce, raw materials, agents, distributors, offers, inventory and sales from one centralized system.
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More AI services
2 servicesAI features, agents, and AI-powered products.
When to build
When should you build an AI agent?
AI agents are useful when a task requires more than generating a single response.
Repetitive Workflows
Tasks that follow a recognizable pattern but still need a judgment call at each step — not simple enough for a fixed script, not novel enough to need a human every time.
Multi-Step Tasks
Processes that require several actions in sequence, where the outcome of one step determines what the next one should be.
API Interactions
Work that means calling several APIs in turn and reasoning about what each response means for the next call.
Research
Gathering, cross-checking and summarizing information from multiple sources into something usable, instead of one search result at a time.
Customer Support
Answering questions correctly from your documentation and knowledge base, and recognizing when a question needs a human instead of guessing.
Data Analysis
Querying your database and turning the result into an insight someone can act on, without a new dashboard for every question.
Document Processing
Reading, extracting and routing information from contracts, forms or reports into the systems that need it.
Internal Operations
Automating internal operations that currently depend on someone manually checking, updating or forwarding information between systems.
Process
AI agent development process
A clear, predictable process — from defining the business problem to deploying and monitoring your agent.
Who I work with
How I can help
Automating a workflow
Build an agent to automate a specific business workflow.
Adding AI to a product
Integrate an AI agent into your existing product or SaaS.
Custom AI solution
Build a custom AI agent for a specific business need.
Business Problem
Understand the specific business problem the agent needs to solve.
Define Agent Responsibilities
Clearly define what the agent should and should not do.
Identify Tools
Determine which APIs, databases, and services the agent needs access to.
Connect Data
Integrate knowledge bases, documents, and data sources.
Build Agent Workflow
Develop the agent logic, tool calling, and decision-making workflows.
Test
Test agent behavior, edge cases, and failure scenarios.
Deploy
Deploy the agent to production with monitoring and logging.
Monitor
Track agent actions, performance, and continuously improve.
Pricing
AI agent development cost
Cost depends on the number of tools, workflow complexity, model usage, RAG requirements, and integrations.
Simple Agent
For single-purpose agents with basic tool calling.
Starting at ₹79,999
- Single-purpose agent
- Basic tool calling
- Simple RAG
- API integration
- 3–5 week timeline
- 30 days post-launch support
Business Agent
For agents with multiple tools and workflows.
Starting at ₹1,49,999
- Multi-tool agent
- Advanced RAG
- Multi-step workflows
- Database integration
- Human approval flows
- 6–10 week timeline
- 30 days post-launch support
Complex Agent System
For multi-agent systems with advanced infrastructure.
Custom pricing
- Multi-agent architecture
- Complex workflows
- Multiple integrations
- Advanced monitoring
- Custom infrastructure
- 10–16+ week timeline
- 60 days post-launch support
Need a custom estimate?
Free project estimate
Tell me what you want to build.
Share a few details, links, or a brief. I’ll review the scope personally and reply with practical next steps and a rough estimate.
What happens next
- 01Tell me about your project
- 02Get a rough estimate
- 03Agree the scope and milestones
- 04Launch with post-launch support
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support@devkitmarket.com
GitHub
LinkedInFAQ
AI agent development — FAQs
Have a different question? Send a short brief directly — no obligation, no sales calls.
support@devkitmarket.comLet's build your AI agent.
Message me on WhatsApp or email me a short brief — I'll reply within one working day with next steps and a rough estimate.