Real customers.Real production.
Kolossus runs in production with named customers across precast manufacturing and AI services. Each one runs a multi-system stack - Tally, custom databases, operational systems - that nobody else was reading well together. This page tells their stories honestly.
A precast concrete manufacturer with operations across multiple plants.
Triranga Infra Projects produces precast concrete components for India's construction sector. Their operational footprint spans plants, vendors, and project sites - with Tally for finance, custom production tracking, and the operational details that live in supervisors' WhatsApp groups.
Triranga's finance and operations teams were spending hours every weekreconciling data across systems that didn't talk to each other. Production runs tracked in custom spreadsheets. Vendor invoices in Tally. Site updates flowing through WhatsApp. Customer orders in a CRM.
Cross-system questions - "what's our actual margin on this project, after raw material variance and freight?" - required someone to pull data from three places, spend half a day in Excel, and produce an answer that was already stale by the time it reached the CFO.
Kolossus reads Triranga's Tally instances, their production tracking spreadsheets, and their custom operational databases simultaneously and in place. No data warehouse. No copies. No migration to a new ERP.
Their finance team now asks questions in plain language - about project profitability, raw material consumption, vendor reconciliation, outstanding receivables - and gets answers in seconds rather than hours. Reports that previously needed a half-day of Excel work now run on demand.
No system at Triranga had to change. Their team continued using the tools they already knew. Kolossus connected to existing systems within the first onboarding call, and was answering production queries by the end of the second week.
The investment was a subscription, not a six-month implementation project. Their existing finance and operations team - without hiring data engineers or analysts - became substantially faster at answering questions that previously required cross-system manual work.
Our questions used to take days to answer. Now they take seconds - and we ask better questions because of it.
Triranga's Founder
An AI services firm using Kolossus on their own operations.
datAIsm builds AI and data products for clients. Choosing Kolossus to read their own internal operational systems is a particular kind of credibility - the people who deeply understand AI for analytics decided not to build their own.
For a company whose business is data, having clean operational visibility into your own systems is non-negotiable. datAIsm runs client engagements, internal projects, and a growing team across multiple operational tools - finance, project tracking, customer communications.
Building their own internal analytics layer was an option. It wasn't the right one. Their engineering time is more valuable applied to client work than to building yet another internal data pipeline.
Kolossus reads datAIsm's operational systems and answers cross-system questions about client engagements, project profitability, and team utilization - without datAIsm having to build any of that infrastructure themselves.
The team gets the operational clarity they need, in seconds, with zero engineering overhead. The right build-vs-buy decision for a team whose engineering time is best applied elsewhere.
Two named customers. More in stealth POC.
We're early. We're being deliberate about who we work with and how loudly we talk about it. Some of our customers prefer to stay private during integration- that's their call, not ours. The named customers above are the ones who chose to be public.
Real production deployments,not vanity logos.
Many vendors fill their customer pages with logos of companies that bought a single seat or attended a webinar. That's not what's on this page.
Every logo above is a customer where Kolossus is genuinely deployed in production, reading their actual systems, answering their actual questions. We grow this list when we have something real to add - not before.