AI agent development on your own data.
An AI agent is more than a chatbot: it can look things up in your documents, call your tools and complete multi-step tasks. We design and build agents for support, sales and operations that are grounded in your data, connected to your systems and safe to put in front of customers.
What’s included
AI Agent Development services
Customer support agents
Answer questions from your help docs, policies and order data, and hand over to a human when needed.
Sales & lead qualification
Agents that respond to enquiries instantly, ask qualifying questions and book calls.
RAG knowledge assistants
Retrieval over your PDFs, wikis and databases with sources cited in every answer.
Tool-using agents
Agents that read and write to your CRM, calendar, spreadsheets or internal APIs.
Document & data agents
Parse, classify and summarise documents and emails into structured records.
Evaluation & monitoring
Test sets, quality checks and logs so you know how the agent performs over time.
How it works
Our AI Agent Development process
- 01
Use case & success criteria
We define exactly what the agent should do, what it must never do, and how we measure it.
- 02
Data & tools
We prepare your knowledge sources and connect the tools the agent can use.
- 03
Build & evaluate
We build the agent, then test it against real questions before anyone relies on it.
- 04
Deploy & refine
Launch on your site, WhatsApp, Slack or internal app, with monitoring and improvements.
Why ParmarSons
Why choose us for AI Agent Development
Tools we use: OpenAI, Anthropic, LangChain, LlamaIndex, PGVector, Python, FastAPI.
Grounded answers
Retrieval with citations reduces made-up answers and makes the agent auditable.
Model-agnostic
We work with OpenAI, Anthropic and open models, and choose per task for cost and quality.
Human in the loop
Sensitive actions require approval, and every conversation is logged.
Related work
Projects we’ve shipped.
FAQ
AI Agent Development questions.
A traditional chatbot follows scripted flows. An AI agent uses a language model to understand requests, retrieve information from your data and take actions with connected tools, handling situations that weren’t scripted in advance.
Retrieval-augmented generation: before answering, the agent searches your own documents or database for relevant passages and uses them as context. It keeps answers accurate and up to date without retraining a model.
It depends on the task. We commonly use models from OpenAI and Anthropic, and evaluate options for accuracy, speed and cost before choosing.
On your website, inside your web app, or in channels like WhatsApp, Slack or email — wherever your customers or team already are.
Related services
Let’s talk about AI Agent Development.
Share a few lines about what you need. We reply within one working day with next steps, not a sales script.
Start a project