Document extraction
Invoices, purchase orders, delivery notes, forms and IDs read into structured records, in Malayalam and English, with review queues for exceptions.
At Infynix, we craft growth engines that inspire and endure.
We build custom AI agents and workflow tools that automate daily administrative tasks. Off-the-shelf AI tools rarely connect to your internal company files or CRM software. AI tools should integrate directly into your daily software to save actual staff hours.
OUR CAPABILITIES IN
Artificial Intelligence & AI Integration
01
The Challenge
02
Our Insight
03
The Solution
04
The Outcome
05
Scale & Optimize
How We Work
01
Measure
We audit your current systems, marketing, and funnels.
02
Design
We architect a custom strategy bridging your exact gaps.
03
Build
We deploy the tech, content, and pipelines required.
04
Launch
We seamlessly roll out the solution with zero downtime.
05
Re-Measure
We track every metric to ensure it meets our strict KPIs.
06
Scale
We optimize the winning channels to compound your returns.
AI for Kerala businesses that does a job: reads the supplier invoices that arrive as WhatsApp photos, answers the questions patients and parents ask at midnight, sorts the enquiries a sales team wakes up to, forecasts the stock a showroom needs before Onam, and flags the exceptions a person needs to see while handling the routine cases itself. Built from Kochi on top of the systems the business already runs, including Tally.
The state is full of AI demonstrations and short of AI that has survived contact with a real business. The gap is not the model. It is the engineering around it: getting the data in, measuring whether the answer is right, keeping a person in the loop until it is, handling Malayalam and Manglish as well as English, and hosting it where the DPDP Act and the client’s contract allow. That engineering is most of the work, and it is what we do.
We are also clear about what we will not build. A model that decides a patient’s treatment, approves a loan on its own or fires off customer messages nobody has reviewed is not a product; it is a liability. The opportunity assessment says which tasks pass the test and which do not, in writing.
We work with trading and distribution companies, hospitals, real estate developers, schools and colleges, NBFCs, retailers and professional firms across Kerala.
What we build
Assistants on your data
Internal and customer-facing assistants that answer from your documents, systems and policies, in both languages, with the sources shown.
Classification and routing
Enquiries, tickets and WhatsApp messages classified and routed to the right person or branch with the context attached.
Forecasting
Demand, cash flow, staffing and stock forecasts built from your history and the Kerala seasonal calendar.
Drafting with review
Routine replies, summaries and documents drafted from your own records for a person to approve.
Computer vision
Quality inspection, counting and document analysis where a camera can replace a manual check.
Search and knowledge
Your documents, policies and archives made searchable and answerable rather than lost in shared drives.
Integration and governance
Built into the ERP, CRM and workflow tools, with accuracy measured, data handled to the DPDP Act and every decision auditable.
Typical engagements and timelines
| Engagement | Typical timeline |
|---|---|
| AI opportunity assessment | 2 to 3 weeks |
| Document extraction pipeline | 4 to 8 weeks |
| Assistant on your data | 4 to 8 weeks |
| Forecasting model | 4 to 8 weeks |
| Ongoing improvement and monitoring | Monthly |
Where AI earns its place
Trading and logistics
Supplier invoices and delivery documents read and matched automatically, in both languages, into Tally.
Hospitals
Insurance pre-approvals, claims documents and patient enquiries triaged, with clinical decisions left to clinicians.
Real estate
Lead qualification and buyer enquiries answered from project information in Malayalam and English, for Kerala and NRI buyers.
Education
Admissions enquiries, fee queries and parent questions answered instantly, with the complex ones routed to staff.
Retail and e-commerce
Demand forecasting across Onam and the monsoon, product content at volume and customer service assistants.
NBFCs and finance
Document processing and enquiry handling within the rules the sector operates under.
How we engage
Opportunity assessment
A paid review of where AI would remove real work in your business, with a costed roadmap and honest verdicts on what would not.
Fixed-scope feature
A defined feature built, measured and launched with review in place.
Ongoing programme
Features added and improved monthly as accuracy and the business allow.
The invoice that arrived as a photo
The most valuable AI feature in most Kerala trading businesses is the least glamorous. Supplier invoices arrive as PDFs, scans and phone photos on WhatsApp, in Malayalam and English, from hundreds of suppliers with hundreds of formats. Someone retypes each one into Tally, and the errors and the delays follow. A document pipeline reads each invoice into a structured record, matches it to the purchase order and the goods receipt, checks the GST fields, posts the clean ones and puts the rest in front of a person with the mismatch highlighted.
Accuracy is measured per supplier and per field, and the review step is removed for the suppliers the model has learned, one at a time, while the exceptions keep going to the accountant.
Any format
Scans, photos and PDFs in both languages, from every supplier.
Three-way match
Invoice, purchase order and goods receipt reconciled automatically.
GST fields checked
Rate, HSN and place of supply validated before posting.
Tally posting
Clean invoices posted through the integration, exceptions to a person.
Answering at midnight in Malayalam
A hospital, a school or a developer receives the same fifty questions hundreds of times: visiting hours, fee structure, which documents to bring, whether a project has a two-bedroom unit left. They arrive on WhatsApp at all hours, in Malayalam, Manglish and English, and from the Gulf as often as from Kochi. An assistant built on the organisation’s own documents and systems answers them instantly, shows where the answer came from, and hands the conversation to a person the moment it goes beyond what it knows.
The assistant is kept inside the organisation’s knowledge by design. It does not browse the internet, it does not guess, and every answer is logged so the team can see what was asked and improve what it knows.
Your knowledge only
Answers grounded in your documents and systems, with sources shown.
Malayalam, Manglish and English
Quality measured on your own examples, not assumed.
Handoff with context
A person takes over with the conversation attached.
Logged and improved
Every question recorded so the knowledge base grows.
Forecasting a Kerala year
Demand in Kerala does not move smoothly. It spikes for Onam and Vishu, dips through the monsoon, surges for the wedding season and shifts with school terms and the December visits from the Gulf. A forecast built on a flat national model misses all of it. A forecast built on the business’s own history, with the Kerala calendar as an input, tells a jeweller what to stock, a distributor what to order and a hospital how to roster, weeks ahead.
We build forecasts from the data the business already has in its ERP, its billing and Tally, present them where planning decisions are made, and compare every forecast with what happened so the model earns its trust.
Kerala calendar built in
Onam, Vishu, monsoon, weddings and school terms as inputs.
Your history
Built from the ERP, billing and Tally data you already hold.
Where decisions happen
Forecasts in the ordering and rostering screens, not a separate report.
Checked against reality
Every forecast compared with the outcome.
Sorting the morning’s enquiries
A sales or admissions team opens WhatsApp and email to a mixture: genuine enquiries, price checks, existing customers with problems, suppliers, spam and the occasional urgent case buried in the middle. Classification and routing read each message, decide what it is and who should handle it, attach the context, and put the urgent case at the top. The team starts the day on the conversations that matter rather than on triage.
For hospitals the same mechanism routes appointment requests, report queries and emergencies differently; for developers it separates NRI buyers, brokers and site-visit requests; for schools it separates admissions, fees and complaints.
Read and classified
Every message typed and prioritised on arrival.
Routed with context
To the right branch, department or person, with the history attached.
Urgent cases surfaced
The emergency or the hot lead at the top, not in the middle.
Measured
Response times and misroutes tracked and tuned.
Further reading
Artificial Intelligence & AI Integration in our other markets
Infynix Solutions is registered separately in India, the United Kingdom and the United Arab Emirates. This page covers India. The same service, written for the other markets:
Artificial Intelligence & AI Integration questions
How can AI help our business?
AI can answer common customer questions, process incoming document data, and automate daily scheduling.
Which task should we automate with AI first?
Usually the one that costs the most hours and follows the clearest pattern: supplier invoice entry into Tally, routine customer questions on WhatsApp, or enquiry triage. The opportunity assessment maps the candidates, estimates the return and lists what we would not build.
Can it read invoices in Malayalam and photos from WhatsApp?
Yes. The pipeline handles scans, photos and PDFs in Malayalam and English from every supplier format, with accuracy measured per supplier and a review queue for the exceptions.
Can the assistant answer in Malayalam and Manglish?
Yes, and the quality is measured on your own real questions before launch rather than assumed, because models differ widely in how well they handle Malayalam.
Where does our data go?
Where the DPDP Act, sector rules and your clients’ contracts allow. Models run in Indian cloud regions or on your own infrastructure where residency is required, and what goes where is written down.
Can AI post entries into Tally?
Yes, with review. Invoices are read, matched and checked by a person until the accuracy for that supplier is proven, then posted through the Tally integration, with exceptions always going to the accountant.
Will AI replace our staff?
It removes the retyping, the triage and the repeated questions. The people spend their time on the cases that need judgement. We do not recommend removing people from the loop where an error would be expensive, and we say so in the assessment.
How do you know it is working?
Accuracy per feature, hours removed, response times and the number of exceptions reaching people, tracked on a dashboard against the baseline from the assessment.
Do we need to build our own model?
Almost never. Off-the-shelf models with your data, good retrieval and the right guardrails do the job. We fine-tune or use open models only where Malayalam quality, cost at volume or residency justify it.
