The language model
The "brain" that understands the message and decides the next step. We choose the model for accuracy, speed, cost and where your data must stay.
AI Agent Development
The AI agent development company that built six agents of its own first
Prilient Technologies is an AI agent development company in India that builds custom AI agents for support, sales, bookings, collections and hiring. Our own platform already runs six complete agents that hand work to each other. We use the same parts to build agents around your workflows, channels and systems.
Book a live AI demo- 6 demo-ready agents on one shared backend
- Human handoff built in
- Registered Principal Entity on TRAI DLT
The difference
A chatbot answers. An AI agent gets the job done.
A chatbot follows a script of menus and fixed replies. When a customer asks something off-script, it loops or gives up. An AI agent understands the request in the customer's own words, then uses your tools to act on it.
Say a patient types, "Can I move my Thursday appointment to Saturday morning?" A chatbot shows a menu. An agent finds the booking, checks Saturday's open slots, offers two options, moves the appointment and sends a confirmation.
Chatbot
- Fixed script
- Buttons and keywords
- Answers only
- Breaks on new questions
AI agent
- Understands free text
- Checks your systems
- Takes actions
- Hands over to a person when unsure
Architecture, simply explained
Six parts inside every agent we build
Agentic AI development is less about the model and more about what surrounds it. These are the parts we design, test and maintain for you.
Tools and APIs
The actions the agent is allowed to take: look up an order, book a slot, create a ticket or send a payment link. Each tool has strict inputs and permissions.
Knowledge and memory
Your FAQs, price lists and policies, which the agent searches before it answers. It also remembers the conversation so customers never repeat themselves.
Guardrails
Rules on what the agent must never say or do, such as inventing a price or promising a refund. Out-of-scope requests are politely declined or passed on.
Human handoff
When the agent is unsure, or the customer is upset, it passes the conversation to your team. The full history and a short summary go with it.
Monitoring and logs
Every conversation, tool call and handoff is logged. Dashboards show what the agent handled, where it struggled and what to improve next.
Use cases
Custom AI agents for the jobs your team repeats
Each example below is a real workflow pattern, built on the same parts as our own agents. Yours will use your rules, your tone and your systems.
Front desk and reception
Answers calls and chats about hours, fees and directions, routes callers and takes messages. After hours, it still books the visit instead of losing the lead.
Typical workflow
- Call comes in
- Agent answers the question
- Offers to book
- Hands off to the Appointment Setter
Customer support
Resolves repeat questions from your knowledge base and raises tickets for the rest. Sentiment detection spots an angry customer early and escalates.
Typical workflow
- Customer asks
- Agent searches your docs
- Answers or opens a ticket
- Escalates with a summary
Sales and lead qualification
Replies to every WhatsApp or web enquiry in seconds and asks your qualifying questions. Hot leads go to sales with notes already filled in.
Typical workflow
- Lead messages
- Agent asks budget, need and timeline
- Scores the lead
- Books a call or updates the CRM
Collections and payment reminders
Sends polite reminders on the schedule and tone you set, and records promises to pay. Disputes and hardship cases go straight to your team.
Typical workflow
- Due date nears
- Agent reminds
- Customer replies
- Payment link, promise-to-pay record or handoff
HR and interview screening
Runs a first-round screen, asking every candidate the same structured questions. Your recruiter gets a summary for each candidate, and people make the hiring decision.
Typical workflow
- Candidate applies
- Agent screens
- Answers summarised
- Recruiter shortlists
Internal operations
Answers staff questions on stock, order status, leave balances and policies from your own systems. It saves your managers from the same ten questions every day.
Typical workflow
- Staff member asks
- Agent checks ERP or HRMS
- Answers
- Logs the request
Integrations
Agents that work inside the systems you already use
An agent is only as useful as the systems it can reach. We connect it through official APIs and webhooks, with each connection limited to the actions it needs.
CRM
Create and update leads, log conversations and assign owners in your CRM, through its API.
WhatsApp Business
Two-way conversations, templates for reminders and opt-in handling on the official WhatsApp Business Platform.
Telephony
Inbound and outbound calls with speech-to-text and natural voices, plus call transfer to a person.
Calendars and booking
Read open slots from your calendar through its API, book, reschedule and cancel, then send reminders.
ERP and accounting
Check stock, order status and outstanding invoices so answers are always current.
Helpdesk and ticketing
Open, update and close tickets with the conversation attached.
HR, attendance and workforce
Answer leave and attendance questions from HR data. Our own Tainaat WorkforceOS already integrates with ZKTeco biometric devices, and VyapaarSense runs HR & payroll.
SMS and email
Reminders and confirmations by SMS and email. Prilient is a registered Principal Entity on TRAI's DLT platform for SMS and voice in India.
Process
From one workflow to a production agent
We prove the agent on your real conversations before it talks to a single customer. You can stop after any stage and keep the work.
-
Discovery
We map the workflow with the people who do it today. We gather sample calls, chats and documents, list the systems involved and agree on success measures.
-
Prototype
A working agent on your real examples, connected to test versions of your tools. You and your team try to break it. Typical time: 2–4 weeks.
-
Pilot
The agent handles a share of live traffic while your team watches and corrects it. We fix every failure and widen the share only when the scores hold.
-
Production and monitoring
Full launch with dashboards, alerts and human handoff. We review conversations monthly, update knowledge and add the next workflow when you are ready.
Test runs by agent version
Illustration
- Right answer
- Right action
- Right tone
- Right handoff
Evaluation and safety
We test agents like software, not like demos
A demo shows the happy path. We build a test set from your real conversations, including rude, confusing and off-topic ones, and score every version of the agent against it. It goes live only when it passes the bar we agreed with you.
- Test sets from real data. Hundreds of past conversations become repeatable tests.
- Scored on what matters. Right answer, right action, right tone and right handoff, each measured separately.
- Least-privilege tools. The agent can only call the actions it needs, with limits on amounts and records.
- Human approval for risky steps. Refunds, discounts and anything irreversible can require a person to approve.
- Privacy by design. Personal data is masked in logs where possible, kept only as long as you choose, and handled with India's DPDP Act, 2023 in mind.
- Regression checks. Every prompt, model or knowledge change re-runs the tests before release.
Technology
The stack behind our agents
We choose tools per project and can run open-weight models on your own servers when data must stay in-house.
Models
- Leading commercial and open-weight language models, chosen per use case
- vLLM (self-hosted serving)
Backend
- FastAPI (Python)
- NestJS
- Node.js
- Laravel
Data and memory
- PostgreSQL
- MongoDB
- Redis
Frontend
- React 19
- Next.js
- React Native
Cloud and DevOps
- Docker
- Nginx
- Secure cloud hosting, with encryption in transit and at rest
Channels
- Phone
- Web chat
- SMS (DLT-registered)
Built and running
Agents and AI products we have already shipped
Own product · Multi-agent platform
AI Agents Platform
Six complete, demo-ready agents on one multi-tenant backend, sharing tenants, configuration, integrations and conversations, and handing off to each other.
- Multi-tenant
- Agent handoff
- Conversations API
Client project · Document AI
DataSwitch
A document processing and personalised data modelling platform we built end to end for our client.
- FastAPI
- vLLM
- PostgreSQL
- React 19
Your options
Off-the-shelf bot, custom agent, or our platform plus customisation
There is no single right answer. It depends on how unusual your workflow is and how deep the integrations go.
| Off-the-shelf chatbot | Fully custom agent | Prilient agent platform + customisation Our approach | |
|---|---|---|---|
| Time to first working version | Days | Longest: everything is built new, with a prototype in 2–4 weeks | Short: six agents already exist, live in 1–2 weeks |
| Fits your exact workflow | Only if your workflow matches the template | Fully | Yes: configured and extended for your rules |
| Takes actions in your systems | Limited to built-in connectors | Any system with an API | Any system with an API |
| Agents hand off to each other | Rarely | Only if you build it | Built in, e.g. Receptionist → Appointment Setter |
| English, Hindi and Hinglish | Varies by vendor | As designed | Designed and tested with your real messages |
| Human handoff and escalation | Basic | As designed | Built in, with full history and summary |
| Who owns the logic and data | The vendor | You | You own your data and configuration |
| Best for | Simple FAQs on a website | Unique, high-value workflows | Most businesses that want results fast without a template's limits |
Pricing
How we price AI agent development
You get a fixed quote after a free 30-minute call, confirmed in writing before each stage, so there are no open-ended bills. Price depends on the number of workflows, channels and integrations.
Discovery and prototype
A fixed fee for mapping the workflow and building a working prototype on your data. If it does not prove its value, you stop there.
Build and launch
A fixed price for the production agent, its integrations, the pilot and the launch. Scope is written down before we start.
Monthly running cost
Hosting, model usage, monitoring and monthly improvements. Model and call or message costs are shown separately, so you can see what you pay for.
FAQs
Questions to ask an AI agent development company
What is the difference between an AI agent and a chatbot?
A chatbot follows a fixed script and can only answer. An AI agent understands free-form requests and uses your tools to act, such as booking a slot or creating a ticket. When it is unsure, it hands over to a person.
What can a custom AI agent actually do for my business?
It can answer calls and chats, qualify leads, book and remind appointments, send payment reminders, screen candidates and answer staff questions. It does this inside your systems, such as your CRM, calendar or ERP. We have built most of these as agents on our own platform.
How long does AI agent development take?
We start with a working prototype on your real conversations, then a pilot on live traffic, then full launch. The timeline depends on your channels and integrations. You get a written plan after the discovery step. Discovery takes 1 week and a prototype 2–4 weeks. A full launch typically takes 6–10 weeks in total.
How much does it cost to build an AI agent?
We quote a fixed price for discovery and prototype, a fixed price for build and launch, and a monthly running cost. The price depends on the workflows, channels and integrations involved. You see the full quote in writing before each stage.
How do you stop an AI agent from making mistakes?
We test every version against a set of your real conversations before release. Guardrails limit what it can say and do, and risky actions can need a person's approval. When it is unsure, it hands the conversation to your team with the full history.
Can the agent talk to customers in Hindi?
Yes. We design agents for English, Hindi and Hinglish, the mix of both that customers actually use. We test them on real sample messages from your business.
Should we use your platform or build a fully custom agent?
If your workflow is close to reception, support, lead qualification, bookings, collections or screening, starting from our platform is faster. If your process is unusual, we build a custom agent from the same parts. We recommend one or the other after discovery.
Is our customer data safe?
Each agent gets only the data and actions its task needs. You decide what is stored and for how long, and personal data is masked in logs where possible. We design with India's DPDP Act, 2023 in mind and sign an NDA on request.
Pick one workflow. We will show you the agent.
Bring a task your team repeats every day. We will map it with you and show how an agent would handle it.
Free 30-min call · Live agent demo on request · NDA on request