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Ernakulam's IT firms, lenders and campuses run on routine digital chores done by hand; AI IT automation hands those chores to software and keeps people for the exceptions.
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Ask an operations head at an Infopark company what the team did last week and much of the answer is chores: creating user accounts, resetting access, reconciling two reports, chasing approvals, copying figures from an email into a system. None of it is difficult. All of it is slow, and given what skilled staff cost in Kakkanad, it is work worth removing.
AI IT automation goes a step beyond scripted bots. It reads unstructured input such as emails, tickets and documents, decides what kind of request it is, carries out the routine steps across your systems and escalates what it cannot settle. We build it around ERPNext where that is your core system, and around your existing tools where it is not.
Case studies
EVM Wheels (part of the EVM Group)
EVM Wheels — 70% of Self-Drive Rentals Now Book Themselves Through the App
Indus Motor Company Private Limited
Indus Motor — ERPNext Cut Stock-Outs 40% Across Showrooms
JPC Enterprises
JPC Enterprises — ERPNext Cut Procurement Delays 40% on Offshore EPC Projects
A service desk spends its first hour reading, tagging and assigning tickets. An AI classifier does this as each ticket arrives, routes it to the right queue, suggests a fix from past resolutions and closes the simple ones, such as access requests, without human help.
Finance teams match bank statements to ledgers, collections to loan accounts and vendor statements to bills. Automation does the matching, clears what agrees and presents only the differences, so month-end becomes a review of exceptions instead of days of checking.
Many Ernakulam firms already have automation of a sort: macros and scripts written by someone who has since left. We replace these with documented, monitored workflows that log every action and alert a named person when something fails.
An example
A software services company at Infopark opens on Tuesday to eighty overnight tickets from customers in three time zones. Before the first engineer logs in, the classifier has read each one, tagged it by product and severity, and routed it to a queue. Nineteen were password and access requests; those were resolved automatically and closed with a note. Three looked like the same outage and were merged, with a summary sent to the on-call lead. In finance, the overnight bank feed has been matched to customer invoices, and the accountant arrives to a list of four unmatched receipts rather than a statement to work through. The operations head spends the morning on a customer escalation instead.
With Ernakulam clients we start by listing the repetitive tasks and timing them, usually over a week at your office. That gives a ranked list: what to automate first and what to leave alone. Our engineers at Infopark build the first workflow, run it alongside the manual process until the results match, then switch over. Each automation has an owner on your side and a log anyone can read.
Start with one process. The first process chosen for payback, with accuracy and time saved measured.
People approve what matters. AI drafts, checks and routes; your team approves anything material.
Audit logs everywhere. Every automated action recorded: what, when and on what data.
Thresholds and fallback. Low-confidence cases go to a person, not through automatically.
Expand. The next process, once the first has proved itself.
The scope and timeline are agreed in writing before work starts.
IT/ITeS and software
Employee onboarding and offboarding across email, code repositories and HR records, ticket triage for support desks, and incident summaries sent to on-call teams for product companies in the Kakkanad parks.
Banking and financial services
Matching of collections against bank entries, document checks on loan files before they reach a credit officer, and scheduled regulatory and management reports assembled automatically, with every step logged for audit.
Universities and colleges
Admission document verification, fee reconciliation against bank receipts, student account provisioning across email, library and learning systems, and routine helpdesk queries answered for campuses at Kalamassery and Kalady.
It overlaps, but goes further. Traditional RPA replays fixed clicks and breaks when a screen changes. AI automation can read free text, handle variation in documents and make limited judgements, and where possible it works through APIs instead of the screen, which is far more stable.
In our experience it changes what they do. The hours spent on copying and checking go, and the same people handle exceptions, customers and analysis. Most firms we meet around Kakkanad are short of skilled hands rather than over-staffed, so freed time is absorbed quickly.
Every workflow has limits on what it may do alone. Anything involving payment, deletion or a customer commitment waits for human approval. All actions are logged, failures raise an alert, and we run new automations in parallel with the manual process before trusting them.
After a first conversation about the process, the systems it touches and how it is handled today, we agree the scope and send you a written quotation. The price, the deliverables and the timeline are fixed against that scope before any work starts, so nothing grows without your sign-off.
You speak to someone who does this work, not a call centre. They ask about the repetitive IT or back-office work, the systems it touches and who approves it now. If it looks like a fit, we agree the scope and put it in writing, with the timeline, before any work starts. If it does not, we tell you.
Infopark, Kochi (Kakkanad)park
Government of Kerala IT park set up in 2004, about 10 km from central Kochi; Phase 1 fully built and Phase 2 (opened 2017) still adding space, with further phases announced.
The state IT park whose service companies run support desks around the clock for overseas clients and generate the ticket volumes that make automated triage pay for itself.
Source: en.wikipedia.orgKINFRA Hi-Tech Park, Kalamasserypark
243-acre KINFRA park near HMT Colony for non-polluting hi-tech industry, with a biotechnology incubation centre, IT/ITES and electronics SEZ space and a gem and jewellery park; about 34 units.
An IT/ITES, electronics and biotech park whose smaller firms cannot staff a full operations team and gain most from automating account provisioning and reconciliation.
Source: kinfra.orgNational University of Advanced Legal Studies, Kalamasseryinstitution
national law university on a 10-acre campus inside KINFRA Hi-Tech Park
A national law university on a campus inside the hi-tech park, an example of the institutions in Ernakulam where admissions, fees and student IT accounts are still provisioned by hand.
Source: en.wikipedia.orgPlaces and organisations are named for local context only. Acube Innovations is not affiliated with or endorsed by them.
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Kochi (Kadavanthra & Infopark) · Thiruvananthapuram · across India & overseas · In business since 2011