+91 9257086308 sales@dqotsolutions.com
Dqot Solutions
+91 9257086308 sales@dqotsolutions.com
Agentic AI · Task Automation

AI Agents Built Around the Way Your Team Works

We build AI agents that plan a task, carry it out in the software you already use and report back, so your team spends less time on routine work. You decide which actions need a person's approval first.

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150+
Software Projects Delivered
8+
Years in Business
7
Client Countries
Agentic AI Development

Agentic AI Development

by DQOT Solutions — Trusted by 75+ Global Clients

LangGraphAutoGenCrewAIOpenAI Agents SDKLlama 3.3RAG Pipelines
India
USA
UK
UAE
Trusted by 75+ businesses across India India USA USA UK UK UAE UAE Canada Canada Australia Australia Rated 4.9/5 on Clutch
What Is Agentic AI?

AI That Finishes the Job You Give It

An AI agent does more than answer a question. You give it a goal, and it works out the steps, uses the tools it needs and keeps going until the job is done or it needs your decision. A chatbot waits for the next message, while an agent can chase an invoice, update a record or prepare a report without being prompted at each step.

We build custom AI agents for the work your team repeats every week. Some jobs need a single agent with access to a few tools. Others need several agents that each handle one part of the task and check each other's results before anything is sent.

What We Deliver

Agentic AI Services We Provide

We design, build and connect AI agents, then keep improving them once your team is using them every day.

🧠

Teams of AI Agents

Some jobs are too big for one agent. We set up several, each with its own role, and coordinate them with a framework such as LangGraph or CrewAI so work passes cleanly from one to the next.

🔧

Agents That Use Your Tools

We give each agent the tools its job needs, such as web search, database queries, email, calendar and your CRM. It can then finish a task without stopping to ask a person for each step.

💾

Memory Across Conversations

We add a vector database such as Pinecone or Weaviate so an agent remembers earlier conversations and decisions. You do not have to explain the same background twice.

🔁

Answers From Your Documents

Agents look up your internal documents and knowledge base before they answer, and check what they find. Their replies are based on your information and not on the model's general knowledge.

🔌

Connected to Your Systems

We connect agents to the business software you already run, such as Salesforce or SAP, and to your own systems through their APIs. Your team keeps working in the tools it knows.

🛡️

Human Approval Steps

You choose the points where a person must review or approve before the agent continues. Sensitive actions such as payments or customer emails wait for that sign-off.

Our Process

How We Build Your AI Agents

We work in six steps and show you the result of each one, so you can ask for changes before we move on.

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1

Discovery & Agent Design

We look at how the work is done today and pick the tasks an agent can take over. Then we decide whether one agent or several will do the job, and which tools and records each one needs.

2

Choosing the AI Model

We choose the AI model and the framework that fit your task, your budget and your data rules. Options range from hosted models such as GPT-4o and Claude to open-source models you can run on your own servers.

3

Connecting Tools & Data

We build the tools your agents need and connect them to your databases and third-party services. An agent can then act inside your systems instead of only describing what should be done.

4

Testing Before Launch

We test each agent on real examples of your work and check its reasoning, its use of tools and how it recovers from errors. We also try to make it fail on purpose, so problems surface before launch.

5

Deployment & Monitoring

We deploy the agents on the cloud you prefer, such as AWS or Azure, and set up a dashboard that shows what they are doing. Alerts tell both of us when something looks wrong.

6

Ongoing Improvement

After launch we review how the agents handled real work and where they slowed down or needed help. We then adjust them so they cost less to run and make fewer mistakes.

Industries & Use Cases

Where AI Agents Help Most

Use Case 1

Customer Service

Support agents answer routine questions, update the customer's record and draft the follow-up email. Harder cases go to your team with the full history attached.

Use Case 2

Sales & Lead Gen

Sales agents research each prospect, write a personal first message and book the meeting. Your CRM is updated as they go, so your sales team can spend its time on conversations.

Use Case 3

Finance & Accounting

Agents read invoices, match them against your accounts and flag anything unusual. Your finance team reviews the exceptions instead of keying in every line.

Use Case 4

Legal & Compliance

An agent reads each contract, compares it with your standard templates and marks the clauses that carry risk. Your legal team receives a short summary to check.

Use Case 5

IT Operations

Agents watch your systems, work out what caused an incident and run the fix you have already approved. They call an engineer when a decision needs human judgment.

Use Case 6

Research & Intelligence

Ask for a briefing and an agent gathers competitor news and industry reports, then writes a summary your managers can read in a few minutes.

Technology Stack

Tools & Technologies We Use

✓ OpenAI GPT-4o✓ Anthropic Claude 3.5✓ LangGraph✓ AutoGen✓ CrewAI✓ LlamaIndex✓ Pinecone✓ Weaviate✓ Python FastAPI✓ AWS Lambda✓ Docker✓ Kubernetes
Why DQOT Solutions

Why Build Your AI Agents With Us

🏆

8+ Years of Building Software

We started in Jaipur in 2018 and have delivered 150+ projects for 75+ clients. The habits we learned on web and mobile products go into every agent we build.

⚡

Short Cycles You Can Review

We build in short cycles and show you a working agent at the end of each one. You can change direction early, while a change is still cheap to make.

🔍

Clear Progress Updates

You get a progress update every week and access to the project board, plus a fuller report each month. You can see what is done and what comes next.

🌍

Based in Jaipur, Clients in 7 Countries

Our head office is in Jaipur, with more offices in New Delhi and Canada. We have worked with clients in 7 countries, including India, the USA, the UK and the UAE.

🤖

AI Where It Is Useful

We use AI tools in our own work to speed up routine jobs. In your project we recommend an agent only where it saves real effort, and tell you when a simpler fix would do.

🤝

Support After Launch

Bug fixes and email support are free for the first month after launch. After that you can keep us on with a paid support package for as long as you need.

FAQs

Frequently Asked Questions

Answers to the questions clients ask most often about AI agents. Can't find yours?

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Traditional chatbots respond to single-turn queries. Agentic AI systems can plan multi-step tasks, call external tools, maintain memory across sessions, self-correct errors, and autonomously execute complex workflows that span hours or days — all without constant human prompting.
A focused single-agent solution takes 4–6 weeks from discovery to deployment. Complex multi-agent pipelines with extensive tool integrations typically take 8–16 weeks. We follow agile sprints with weekly demos so you see progress throughout.
For most enterprise use cases, we recommend GPT-4o or Claude 3.5 Sonnet as the backbone LLM due to their strong tool-use and reasoning capabilities. For cost-sensitive high-volume tasks, we fine-tune open-source models like Llama 3.3 or Mistral.
We implement Human-in-the-Loop (HITL) checkpoints, hard-coded action boundaries, and approval gates for high-stakes operations. All agent actions are logged in an immutable audit trail, and we configure confidence thresholds that trigger human review when uncertainty is high.
Yes. We build custom tool wrappers and use MCP (Model Context Protocol), REST APIs, webhooks, and SDK integrations to connect agents with Salesforce, HubSpot, SAP, Slack, Google Workspace, Jira, and virtually any system with an API.
The return depends on how much work the agent takes over and how often that work comes up. Before we build, we estimate the hours your team spends on the task today and what the agent will cost to run, so you can compare the two. We do not quote a return figure until we have seen your process.

Have a Task You Want an AI Agent to Handle?

Tell us about it and we will reply within one working day. The first consultation and the quote are both free.

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