Nine in ten organizations now use AI regularly. Only 6 in 100 capture significant value. They are the ones that learn fastest which problems AI should solve, then redesign the workflow around the answer.
AEQUITOUS is an enterprise AI engineering company. In 3, 5 or 9 weeks we tell your leadership team whether AI can solve a business problem, then engineer it into an enterprise capability your team owns.
Of every 100 organizations. Source: McKinsey, The State of AI in 2026.
We build. We ship. We stand behind it.
Founded 2025
Enterprise processes are built for certainty. AI value comes from fast evidence on a real problem. 359 gives leadership that evidence before the deep investment of time, budget and people.
Illustrative, drawn from enterprise program experience.
Answers in weeks.Choose a 3, 5 or 9 week engagement. Each one is standalone, so you start where your decision is.
Fixed time, fixed price, fixed outcome.One measurable outcome, with its baseline and target, defined at the start.
Your environment.Built in your cloud and your repositories, to your standards, alongside your engineers.
Each engagement is standalone, with its own fixed scope, price and outcome. Choose one, or combine them.
Should we use AI here?
For an open question. Leadership wants evidence before committing budget.
A clear go, refine or redirect call, backed by evidence.
How should it work?
For a chosen use case that needs to prove value inside the real workflow.
The question moves from “Can AI do this?” to “Is it worth deploying?”
Which system scales?
For enterprise scale deployment, in your environment, to your standards.
Your cloud. Your repositories. Your standards.
Clear value, ready to build
The answer in three weeks
Equip internal teams
Reshape the outcome first
Where an opportunity sits on value and complexity decides where to start.
Placement is decided by the value at stake, data readiness, a named business owner, the risk profile and the expected cost per outcome.
Production AI systems for operations where every transaction carries financial risk. We proved each one on our own platforms first, and the same patterns apply to finance, operations and customer workflows in any enterprise.
Financial operations · proven on GaadiKharcha
Revenue was leaking between sales channels, banks and vendors, and nobody could see where. We built the AI engine that matched every sale to its settlement and cost, and recovered 8 to 15 percent of revenue.
One data layer that ingests sales from every channel, settlement reports, bank statements, vendor costs and toll data. A matching engine pairs every sale with its settlement and cost, then flags mismatches, missing settlements and leakage.
Reconciliation cut from 6 hours to 30 minutes. 8 to 15 percent of revenue leakage recovered. $50M+ reconciled.
Document intelligence · proven on GaadiKharcha
Partner reports arrived as PDFs in layouts that changed without notice, and people typed them in by hand. We replaced that with an agent that reads every report the moment it lands.
A coordinate based extraction parser that reads each layout into clean, structured records, plus a desktop agent that watches for new reports and ingests them automatically into the reconciliation engine.
Zero manual entry from report to reconciliation.
Agentic AI · proven on Rentofly
A new market launch needed a marketing team and there was no time to hire one. We deployed five specialist agents and one manager agent in under a week, and marketing now runs end to end.
A multi agent system: five specialist agents, each owning one part of the marketing workflow, coordinated by one manager agent.
Engineered and deployed in under a week. Marketing runs end to end on agents.
Risk and trust · proven on Rentofly
Landlords could not judge a tenant quickly, and good tenants and good listings kept missing each other. We built the credit score and the matching engine behind 1,500+ property agents.
A rental credit score algorithm for tenant verification and a matching engine that pairs tenants with listings, with digital agreements on iOS and Android.
1,500+ property agents and 5,000+ listings on the platform.
Dispatch · proven on GaadiKharcha
Jobs were handed out by phone: slow, unfair to drivers and blind to which vehicles were free. Now a real time queue and an AI allocation engine assign every job automatically.
A QR based real time queue. Drivers check in with a scan, and the engine assigns each job automatically on queue position, driver availability and vehicle availability. Allocation is optimized with AI.
Jobs assigned automatically, in queue order.
Unit economics · proven on GaadiKharcha
Managers knew their revenue but not what each vehicle or route really earned after fuel, tolls, drivers and maintenance. Now they see it in real time.
A unit economics engine that combines fuel intelligence, maintenance, driver costs and receivables into per vehicle and route level profit and loss, with a cash flow view.
Real time profit for every vehicle and route.
Rapid engineering · proven on GaadiKharcha
Staff and attendance lived on paper and group chats, outside the system that runs the business. With AI assisted engineering we shipped a full module in 3 days, not a quarter.
A light HR system with staff records and attendance, built inside the platform with AI assisted engineering and shipped as an add on module.
Specified, engineered and deployed in 3 days.
Which layer should AI actually change?
A single cloud platform now offers more than 100 foundation models. Choosing one is the easy part. AEQUITOUS engineers the whole system around the outcome, for a clear cost per business outcome: per invoice, booking, case or decision. We are model agnostic and vendor agnostic by design.
Source: AWS Bedrock foundation model catalog.
Every engagement runs on the engineering system behind our own platforms, GaadiKharcha and Rentofly: AI assisted development, automated testing and a release every 15 days.
Both serve paying operators at scale and share one architecture: AI intelligence, reconciliation infrastructure, operator dashboards and an API integration layer. This is the engineering we bring to your enterprise.
Rental credit and marketplace platform
Trust infrastructure for the rental ecosystem. Rental credit scores, tenant verification and digital agreements on iOS and Android, with an AI agent team running marketing for the UAE market.
Fleet FinOps platform
AI driven financial operations for fleet and bus operators. Bookings, fuel, tolls, drivers and banks reconciled in one place, so operators see what they earned and where money leaks.
One path, one accountable team. You can stop after any stage, and everything we build ends up in your hands.
Tests fit with you and recommends Prove, Pilot or Produce.
Shares the problem, the outcome needed and who owns it.
You getA recommendation on where to start
Signs a mutual NDA before any data is shared.
Signs on paper your counsel recognizes.
You getProtection in place before any data moves
Defines the baseline, target, quality bar, timeline and fee in one statement of work.
Agrees the outcome and signs. Billed in US dollars.
You getFixed scope, outcome, timeline and fee
Frames the outcome, builds candidate architectures, tests them on your data and measures the cost per outcome.
Gives access to the data, names one accountable owner and makes the go, refine or redirect call.
You getAI Opportunity Blueprint, working proof, architecture recommendation and economics
Validates the solution inside the real workflow and measures cycle time, accuracy, cost, adoption and effort removed.
Provides real enterprise data and real users.
You getValidated solution, evaluation results, business case and a blueprint to scale
Builds, runs and transfers: architecture, security, integration, evaluation, observability and cost controls.
Hosts it in your cloud, to your standards.
You getAn enterprise AI capability in your cloud and repositories
Delivers documentation, runbooks and training for your engineers.
Owns the code, all project IP and the data, and operates it.
You getEverything, running in your cloud and operated by your team
Each engagement carries one fixed fee for consulting and engineering, scoped to one outcome and one timeline.
Every engagement is senior led, from the first conversation to handover.
Founder and Chief Executive Officer
Vipin founded AEQUITOUS after 19 years engineering enterprise systems for global financial services at Capgemini, Genpact Headstrong and Quinnox, where he was VP Technology Solutions. Alumnus of IIM Ahmedabad. Under his leadership AEQUITOUS built GaadiKharcha and Rentofly, the two platforms behind our proof. He personally leads architecture and delivery on every engagement, from the first conversation to handover.
The 359 Model is the AEQUITOUS way to take an enterprise from an AI question to a working AI capability. Prove (3 weeks) answers whether to use AI, Pilot (5 weeks) shows how it should work with real users and real data, and Produce (9 weeks) deploys it at enterprise scale in your cloud. Each engagement has fixed time, fixed price and a fixed, measurable outcome.
A proof of concept, which we call Prove, is a 3 week engagement that tests whether AI can solve the problem on your data and ends in a go, refine or redirect decision. A pilot is a 5 week engagement that validates the chosen solution inside the real workflow, with real users and real data, and produces a business case and a blueprint to scale.
Evidence takes 3 weeks with Prove. A validated pilot takes 5 weeks. A production deployment in your cloud takes 9 weeks with Produce. You can start at the stage that matches your decision, and each engagement stands alone.
Yes. Delivery is remote, with working hours overlap agreed for your team. Contracting and invoicing are in US dollars, and the work runs in your cloud under your access controls.
You commit to one engagement at a time. Prove, Pilot and Produce are each standalone. Start with Prove when the question is open, Pilot when the use case is chosen, and Produce when you are ready to deploy at scale.
Before we start, we define one measurable outcome: the baseline, the target, the quality bar the system must hold, the target cost per outcome and the delivery date. We keep working on the agreed scope until it is delivered, at the same fixed price, with changes handled through an agreed change process.
Book a 30 minute leadership call. We test fit, recommend Prove, Pilot or Produce and send a scope with outcome, timeline and fixed fee within days. Contracting is in US dollars.
The fixed fee covers consulting and engineering. Cloud infrastructure, AI model usage, travel, third party licenses and other costs are billed separately at actuals, ideally on your own accounts so you keep full visibility.
Whichever fits the outcome. We are model agnostic and vendor agnostic, and we work across frontier, specialized and open models on the major cloud platforms. The architecture is chosen on quality, latency, cost and control, and tested on your data.
You do. Code lives in your repositories, the system runs in your cloud, your data stays in your environment, and all project IP belongs to you. We document the architecture and train your team so you can operate and evolve it.
We work inside your environment and to your standards. Access, data boundaries, audit, evaluation and observability are designed in from the start, and every deployment passes through your own security and release processes.
We prefer it. Your engineers work with us from the start, which makes the handover a natural continuation of the work.
Every engagement is senior led. Choose 3, 5 or 9 weeks, and know before you invest deep.