AI automation · India

AI automation and implementation for Indian businesses.

From our office in Kozhikode, Kerala, Pyalm helps Indian businesses put AI to work on real operations — documents, customer conversations, and internal knowledge — at a cost that makes sense for Indian margins.

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Kozhikode, Kerala, India

AI that fits Indian operations

Indian SMEs and mid-size companies usually run on a mix of Tally or Zoho, WhatsApp, Excel, and email. AI works best here when it removes manual steps between those tools rather than replacing them:

GST invoices and purchase bills — extracting line items, GSTINs, and tax amounts into Tally, Zoho Books, or your ERP
WhatsApp customer support — AI drafting answers in English, Hindi, Malayalam, Tamil, and other languages, with staff approval
Lead handling — qualifying IndiaMART, website, and WhatsApp enquiries and routing them to the right salesperson
Internal knowledge — answering staff questions from product catalogues, price lists, and SOPs

Cost-conscious by design

AI costs are driven by model choice and volume. For high-volume Indian workloads we route simple tasks to smaller, cheaper models, cache repeated work, and reserve the strongest models for tasks that need them. We report cost per processed document or conversation, so the economics stay visible. Our AI development cost guide explains the drivers.

DPDP Act-aware data handling

The Digital Personal Data Protection Act, 2023 sets obligations for how personal data is collected, used, and protected. Our implementations minimise personal data sent to models, keep processing purposes narrow and documented, log access, and support self-hosted models where data should not leave your environment. Your legal team makes the final compliance call; we make sure the system supports it.

Local team, global standards

Our engineers are based at HiLITE Business Park, Kozhikode, and we deliver for clients across Kerala, Bangalore, Chennai, Mumbai, Delhi NCR, and internationally. The same team builds AI automation for UAE and global clients, so Indian projects get the same evaluation, guardrails, and monitoring practices.

What we deliver

AI implementation & automation, end to end.

AI opportunity assessment and implementation roadmap
Internal copilots and knowledge assistants over your documents
Document extraction for invoices, POs, contracts, and forms
Customer-service, email triage, and lead-response automation
Model, API, CRM, helpdesk, ERP, and database integrations
Evaluation sets, guardrails, human approval, and cost monitoring

Selected work

Built and running in production.

All case studies

Real estate & property management · Global

Retail property collections team

A stakeholder-ready product prototype that ranks rent decisions by tenant sales and affordability, with evidence, approvals, and an audit trail.

Read the case study Marketing automation · Global

Pyalm 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 study

Frequently asked

Questions from India clients.

Can the AI work in Malayalam, Hindi, or other Indian languages?

Yes. Leading models handle major Indian languages, including code-mixed text. We test quality on your real messages before going live and keep a human approval step where accuracy matters.

Can it read GST invoices and push data to Tally or Zoho?

Yes. Document AI can extract GST invoice fields and post them to Tally, Zoho Books, or other systems, with low-confidence fields routed for review.

Where is your team located?

Our office is at HiLITE Business Park, Kozhikode, Kerala. We work with clients across India in person or remotely.

What can Pyalm automate with AI?

Common projects include knowledge assistants, document processing, customer-response support, email triage, content workflows, classification, data extraction, and AI steps inside wider business processes.

Can AI automation connect to our existing systems?

Yes. The useful part is usually the connection between models and your CRM, helpdesk, documents, databases, ERP, APIs, or internal applications.

How do you reduce AI errors?

We use bounded tasks, grounded source material, evaluation cases, validation rules, confidence thresholds, human approval for sensitive actions, and monitoring after launch.