Answers in seconds, from your sources
Customers and staff get accurate answers drawn from your own documents, with citations they can check.
AI agent and chatbot development, grounded in your data.
Pyalm builds AI assistants and agents that know your business—answering from your documents, taking approved actions in your tools, and handing over to people when they should.
Kozhikode, India Dubai, UAE Global delivery
Agents that complete tasks
Book appointments, check order status, create tickets, or update records through approved tool connections.
Clean hand-off to people
Conversations escalate with full context when the assistant is unsure, the topic is sensitive, or the customer asks.
What we can deliver
A complete, usable solution—not an isolated feature.
- Use-case design, conversation flows, and escalation rules
- Retrieval-augmented generation (RAG) over documents, sites, and databases
- Website, WhatsApp, and internal-tool chat interfaces
- Tool-using agents connected to CRM, booking, order, and ticket systems
- Evaluation sets, red-team testing, and safety guardrails
- Analytics on resolution, escalation, cost, and unanswered questions
Chatbot, RAG assistant, or agent: what is the difference?
| Type | What it does | Good for |
|---|---|---|
| Scripted chatbot | Follows fixed menus and rules | Simple FAQs, lead capture |
| RAG assistant | Retrieves relevant passages from your documents, then answers with citations | Support, policies, product knowledge |
| AI agent | Plans steps and calls tools — APIs, databases, booking systems | Order status, bookings, ticket creation, data updates |
Most businesses need a RAG assistant first, then add agent actions one tool at a time. We explain the trade-offs in AI agents vs chatbots vs automation.
WhatsApp-first assistants for the Gulf and India
In the UAE, Saudi Arabia, and India, customers expect to message a business on WhatsApp. We build assistants on the official WhatsApp Business API with template messages, opt-in handling, human takeover in a shared inbox, and Arabic or regional-language support. Our sister product Tenreply provides the WhatsApp infrastructure, so we have operated these channels in production.
Built so you can trust it
Hallucinations are a design problem, not a mystery. Our assistants answer only from retrieved sources, say when they do not know, refuse out-of-scope requests, and log every conversation for review. Agent actions use narrowly-scoped tool permissions and require confirmation for anything irreversible. We also run evaluation sets before each release so changes to prompts or models never silently reduce quality.
Selected work
Built and running in production.
Real systems we have designed and delivered — client projects and products we operate ourselves.
Wedding photography platform
Photographers upload thousands of event photos; guests scan a QR code, take a selfie, and instantly see every photo they appear in.
Read the case studyPyalm HQ
An automation console that turns filtered industry news into AI-written LinkedIn and Instagram posts and publishes them on a schedule.
Read the case studyDelivery approach
Clear decisions from discovery through improvement.
Scope, evidence, and ownership remain visible throughout the project so the finished system can be operated—not just demonstrated.
Scope
Choose the conversations and actions worth automating and define what must always go to a person.
Ground
Prepare and index knowledge sources, permissions, and the tools the agent may call.
Evaluate
Test against real questions and adversarial cases until accuracy and refusal behaviour are acceptable.
Launch & learn
Release to a limited audience, review transcripts, and expand coverage based on unanswered questions.
Frequently asked
What to know before we begin.
Can the chatbot answer from our own documents?
Yes. We index your PDFs, web pages, help-centre articles, and database records so the assistant answers from them and cites the source.
Can it work on WhatsApp?
Yes. We build on the official WhatsApp Business API with opt-in, templates, and human takeover, and can also deploy the same assistant on your website and internal tools.
Does it support Arabic?
Yes. Current models handle Arabic and many Indian languages well. We test the specific language and dialect mix your customers use before launch.
What stops the AI from making things up?
Answers are grounded in retrieved sources, low-confidence responses escalate to a person, and we evaluate against real and adversarial questions before every release.
Can an AI agent take actions in our systems?
Yes, through approved API connections with narrow permissions. Sensitive or irreversible actions require confirmation from the user or a staff member.
Guides on this topic
Practical reading before you decide.
- AI Implementation for Business: A Practical Roadmap (2026)
A step-by-step roadmap for implementing AI in a real business — choosing the first use case, preparing data, building with guardrails, measuring ROI, and scaling beyond the pilot.
- How Much Does AI Development Cost? UAE, India and US Compared (2026)
Indicative 2026 cost ranges for AI chatbots, RAG assistants, document AI, and AI agents in the UAE, India, and the US — plus the running costs and the factors that move the price.
- AI Agents vs Chatbots vs Automation: Which Does Your Business Need?
Scripted chatbots, RAG assistants, AI agents, and workflow automation solve different problems. A plain-English comparison with examples, risks, and a decision guide.
- AI in Logistics: 7 Practical Use Cases and the Data They Need
From document extraction to ETA risk and demand planning, here is where AI can help logistics teams—and what must be in place first.
- A Practical AI Playbook for Founders: Start With Workflows, Not Hype
How founders can choose useful AI projects, put human review in the right place, measure value, and avoid building an expensive demo.