Real AI systems, in production.
Eighteen AI, automation and analytics case studies from Finzarc — real enterprise builds in production, three told in depth and the full ledger below. Every claim ships with a log attached.
Fourteen regions, fourteen versions of the truth. Sales data reconciled by hand, reported a month late — decisions made on gut and last quarter's export. We wired every source into one live layer of analytics and business-intelligence systems and put demand forecasting on top. Now the weekly commercial call opens with a number everyone trusts, and a ranked list of exactly where revenue is leaking.
“The effort put in and the accountability taken by the team was unparalleled.” — COMMERCIAL LEADERSHIP
Client reporting ate a full day, every week — pulling platform numbers, reconciling spreadsheets, formatting decks. Our AI agents and agentic automation now run the entire loop: pull, reconcile, publish, deliver, before the team's first coffee. The humans went back to strategy. The reports stopped having typos.
List prices, costs, standard costs, customer and sales values were scattered across a dozen sources — so leadership couldn't analyse the business coherently. We built the data-engineering and analytics layer: Python pipelines that ingest every pricing dataset into one single-source database, surfaced through leadership dashboards. Now a 121-year-old manufacturer runs off one number, not fourteen versions of it.
Across eighteen delivered builds, Finzarc has returned 60,000+ hours a year, surfaced ₹4.2Cr in recoverable revenue, and cut ₹10Cr/yr in bad-stock write-offs by ~90% — every figure logged, every build in production.
Names withheld on purpose — we'll walk you through any of them on a call. Grouped by business vertical — marketing, sales & pricing, finance, supply chain & ops, HR, leadership & BI, field ops, and product — and filterable by industry. Every card opens the full build story — or explore every service we ship to see how they're built.
No builds match that filter yet.
Yes. Every build in this ledger ships with the metric attached — +27% revenue and margin from 30% to 38% (BrandOptix), ₹10Cr/yr write-offs cut ~90% (GRN reconciliation), 60,000+ hours returned a year (Performix). Eighteen production systems, numbers logged, not rounded.
Eighteen production builds across agentic automation, analytics & BI, data pipelines, pricing and revenue systems, supply-chain control towers, GenAI apps, and computer-vision field-capture tools. See the full range on our solutions page.
Consumer goods & FMCG, industrial & energy, marketing & e-commerce, pool & wellness equipment, and education & research — for Fortune 500s and century-old manufacturers. Filter the ledger by industry or business function to see each.
By agreement. These are live production systems for enterprises that prefer their edge stays quiet. The builds, the methods and the numbers are real — we'll walk you through any of them, named, on a call.
First delivery in about three weeks. Hi Langee went from idea to a store-ready GenAI app in 21 days; the first module of an organisation-wide GPT was live in two weeks. Working software over promises of future.
Bring the problem, leave with a scope. Book a 30-minute call with the founders, Piyush Kumar and Abhinav Tripathi — the people who build it are the people on the call.
Every Finzarc build is scoped around the single business number it should move, so ROI is defined before the work starts, not estimated after. Across the ledger that's meant +27% revenue with margin from 30% to 38%, ₹10Cr/yr write-offs cut ~90%, ₹4.2Cr in recoverable revenue surfaced, and 60,000+ hours returned a year. Because first delivery is about three weeks, payback usually starts within the first month or two.
Finzarc scopes a fixed first version on the call, priced against the metric it should move rather than billed by the open-ended hour. Most engagements start with one focused build — an automation, an analytics layer or an MVP — and because you see working software in about three weeks, you can judge the return before any larger commitment. Bring the problem and we'll put a real number on it.