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AG Brain · Operating intelligence

One Brain that runs your entire business.

AG Brain is the operating-intelligence layer that reads across every system you already run — SAP, Oracle, Tally, Zoho, your CRM, the spreadsheets and the WhatsApp threads — so you can see and act on the whole business in real time, instead of finding out at month-end.

One Brain per clientReads SAP, Oracle, Tally, ZohoDeterministic numbersDPDP-mappedData stays in India
Book the 10-Day Signal Audit See how the Brain works
How it works

Your systems already hold the answer. Nothing can see across them.

Every enterprise records far more than it can read. The ERP knows the cost, the CRM knows the customer, the warehouse knows the stock and the WhatsApp thread holds the approval — and no single layer can hold all four at once, so the business is understood a month late, in a meeting, from four spreadsheets that disagree.

AG Brain sits across those systems as one memory of the whole business. It learns what normal looks like for you, sets that as the baseline, and lets every agent, briefing and answer reason over connected truth rather than over an isolated row. The systems stay exactly where they are.

System of record → system of action. Hindsight → real-time foresight.

What you record — disconnected◆ One Brain
SAPOracle ERPTallyZohoCRMWhatsAppEmailExcel
Reads across every system
The Brain · enterprise context engine One memory of your whole business.

Learns “normal” · sets the baseline · reasons across

Turns into
Finance engineRevenue engineMorning briefingsWhatsApp assistantReal-time answers
System of record → system of actionHindsight → foresight
Start with the problem, not the technology

Different sector. Same problem.

You will recognise it before we name the industry. These are the four sentences we hear most often in a first conversation.

“My team is on the phone all day confirming what the system already knows.”
Heard from an operations head

Hundreds of confirmation calls a day, to re-read data the ERP already holds.

“The same product earns differently across my companies, and nobody can compare it.”
Heard from a multi-entity CFO

Margin invisible across entities, because no two of them share a master.

“My biggest blind spots only show up at month-end, when it is already too late to act.”
Heard from a services business

Daily exposure, seen thirty days late.

“Every department has a dashboard. Not one of them agrees with the others.”
Heard from a group CIO

Four versions of the truth, and a meeting to reconcile them.

The difference

Everyone is selling a swarm of agents. We build the Brain that makes them trustworthy.

AG Brain is not a chatbot, a dashboard or a wrapped language model. It is one enterprise context engine per client — a persistent semantic graph of your whole business. The agents are the hands.

What is mostly on offer

A swarm of AI agents.

Useful, increasingly commoditised, and only ever as good as the context someone hands them each time. The work moves; the memory does not. Every session starts from zero, so nothing compounds and nothing is attributable.

The difference
What AG Brain deploys

One Brain per client.

An enterprise context engine that learns what normal looks like for your business, sets the baseline, and lets every agent reason over connected truth. That memory is what makes a gain attributable and an answer defensible — and it compounds every day you run it.

01

A context graph, not a prompt

One semantic layer over your SAP, Oracle, Tally and Zoho data, so an agent reasons over connected entities — this customer, this SKU, this entity, this contract — instead of whatever rows someone pasted into it that morning.

02

It learns your baseline

The Brain learns what normal looks like for your business before it claims anything is abnormal. That is what makes a deviation visible the day it appears, and what makes an improvement attributable to you rather than to the season.

03

Deterministic where it counts

Finance and operations arithmetic is computed, not generated. Language models write the narrative and never the number, and every figure carries the source row it came from. A number a CFO cannot trace is a number a CFO will not sign.

04

Yours, and isolated

One Brain per client, in an environment dedicated to you. Data does not cross tenants and is not used to train anyone else’s model. Hosting location is agreed in writing before deployment.

What it reads

It runs across the systems you already paid for.

No rip-and-replace, and no migration project to justify first. The Brain reads your estate as it stands — and what it cannot read, we tell you during the audit rather than after the contract.

SAPECC and S/4HANA — finance, materials, sales and distribution
Oracle ERPE-Business Suite and Fusion Cloud
TallyTallyPrime ledgers, vouchers and masters
ZohoBooks, CRM, Inventory and People
CRM & helpdeskSalesforce, HubSpot, Zoho CRM, Freshworks
Operational systemsWMS, HIS, LMS, POS and marketplace panels
WhatsApp & emailWhere the confirmations and approvals actually happen
SpreadsheetsThe workbook that quietly became a system of record
By problem, not by industry

What your systems cannot see, turned into what you act on first.

Four sectors, one pattern. Each card sizes the opportunity as a worked example on a stated set of assumptions — so you can replace our revenue figure with yours and re-run it. These are models, not client results: we publish no client number we cannot evidence.

A hospital corridor with staff at a nursing station
HealthcareHospitals, clinics and diagnostics networks
What becomes possible

Clinical, billing and inventory systems stop disagreeing about the same patient and the same day.

How the Brain helps

The Brain reads across the HIS, the LIS and the billing ledger and resolves them onto one patient and one encounter, so an unbilled procedure, a consumable issued against a discharged patient, or a claim about to miss its filing window surfaces the day it happens rather than in the month-end reconciliation. Where CuraOS is deployed it is already that record; where it is not, the Brain reads whichever HIS is in place.

Sizing the opportunity — worked example

300-bed hospital with an attached diagnostics network, ₹180 cr annual revenue, ₹60 cr of it billed to insurers

Unbilled procedures, consumables and services
2.0% of ₹180 cr₹3.6 cr
Claims lost to the filing window, half of an 8% denial rate
4.0% of ₹60 cr₹2.4 cr
In view in year one₹6.0 cr a year

Revenue the hospital had already earned and simply never billed, because the procedure sat in the HIS and the charge never reached the ledger.

A revenue leak is almost never hidden. It is split across three systems.
A worker scanning inventory in a warehouse aisle
ManufacturingMulti-plant and multi-entity manufacturers on SAP or Oracle
What becomes possible

The monthly workbook becomes a live model, and every figure in it traces back to its source row.

How the Brain helps

One SKU master, one cost model and one customer master across entities, so the same product can finally be compared margin-by-margin between companies. The Brain sets a daily baseline for yield, scrap, discount and freight, and pushes the deviation to the plant head who can still act on it — not to a dashboard nobody opens.

Sizing the opportunity — worked example

three manufacturing entities on SAP, ₹1,200 cr combined revenue, one shared product catalogue

Discount and price creep, invisible across entities
0.6% of ₹1,200 cr₹7.2 cr
Yield and scrap drift caught daily instead of monthly
0.3% of ₹1,200 cr₹3.6 cr
In view in year one₹10.8 cr a year

None of this is theft or error. It is the same SKU quietly earning different margins in three companies that have never shared a cost model.

Leaders trust a number they can trace.
Parcels moving along a sorting conveyor in a fulfilment centre
E-commerce & retailMulti-marketplace sellers and D2C brands
What becomes possible

True contribution margin per SKU, per channel, after the deductions that marketplaces apply weeks later.

How the Brain helps

Marketplace settlements, returns, ad spend, warehousing and shipping are reconciled against the order and the ledger, so a SKU that looks profitable at list price and loses money after RTO and commission is identified as such. Return abuse patterns and stuck settlements surface as exceptions rather than as a quarterly surprise.

Sizing the opportunity — worked example

₹240 cr GMV across three marketplaces and a D2C site, ₹18 cr annual ad spend

Settlements stuck or short-paid, never reconciled
1.0% of ₹240 cr₹2.4 cr
Ad spend behind SKUs that lose money after RTO and commission
20% of ₹18 cr₹3.6 cr
In view in year one₹6.0 cr a year

The ad spend is not wasted because the campaign failed. It is wasted because the SKU was profitable at list price and negative after the deductions that land six weeks later.

The bestseller and the most profitable product are rarely the same SKU.
The business district skyline of an Indian financial centre at dusk
Financial servicesLenders, NBFCs, brokers and insurers
What becomes possible

Portfolio, collections and customer exposure read from one connected truth, with the regulatory evidence attached.

How the Brain helps

The Brain joins the lending or policy system, the collections log, the KYC record and the ledger, so exposure by cohort, early-warning signals and the queue of expiring KYC and mandate records are all visible against a daily baseline. Because the same firm maps the deployment to DPDP obligations, the audit trail is designed in rather than reconstructed later.

Sizing the opportunity — worked example

NBFC with ₹2,500 cr AUM and a 2.8% gross NPA book, roughly ₹70 cr stressed

Stressed accounts surfaced 30 days earlier by a daily baseline
₹70 cr in view sooner—
Cured through earlier contact, at a conservative 12%
12% of ₹70 cr₹8.4 cr
In view in year one₹8.4 cr a year

Collections teams rarely lack effort. They lack thirty days, and the signal that would have told them which account to call first.

In a regulated book, the answer and the evidence for it are the same deliverable.
Governed by default

A Brain that reads everything has to be trusted with everything.

This is the part most operating-intelligence pitches leave for the security review. Avisha Global builds AI, tests AI and does DPDP compliance work with the same team, so your Brain arrives already governed rather than governed afterwards.

Residency

Your data stays where you agreed

Hosting location is written into the contract before deployment, not discussed afterwards. For Indian businesses that normally means infrastructure in India. Your data is never used to train a model outside your tenant.

DPDP

Mapped to obligations, not to a logo

The same team that builds your Brain maps it to the Digital Personal Data Protection Act: purpose, consent, retention and erasure, recorded in an AI system register an auditor can actually read.

Adversarial testing

Red-teamed by the people who built it

Agents that read enterprise systems are an attack surface. Prompt injection, tool abuse and data exfiltration paths are tested against OWASP LLM Top 10 and MITRE ATLAS before go-live, and again on change.

Human checkpoints

Autonomy is earned per workflow

The Brain reads broadly and writes narrowly. Any consequential or irreversible action carries a named human checkpoint until that workflow has earned its autonomy — and the checkpoint is a setting you control, not a promise we make.

How we test AI systems DPDP compliance
The way in · low commitment

Do not take our word for it. Let us size the recoverable value in ten days.

The 10-Day Signal Audit is a fixed-fee, read-only diagnostic. You hand us a data export, nothing in production is touched, and you get back a department-by-department audit and a number you can defend — before you commit to anything.

Day 1–2

Data handover

You send an export. Read-only, under a signed NDA and processing terms. Nothing is installed and nothing in production is touched.

Day 3–8

Shadow run

We stand the Brain up against your data in an isolated environment, learn your baseline, and find where the money and the time are actually going.

Day 9–10

Readout

A working session with your leadership. We walk the findings department by department and leave the written audit behind.

01A department-by-department audit, every line stated in ₹.
02The top three recoverable opportunities, ranked, each with the evidence behind it.
03A fixed-fee deployment plan — and if you proceed, the audit fee is folded into month one.
04Your first morning brief, generated live from your own data, on your phone.
Book the 10-Day Signal Audit Talk to an engineer first
FAQ

Before you book the audit

Neither. A chatbot answers from whatever context it is handed in that session; a dashboard shows you a number and leaves the interpreting to you. AG Brain is a context engine: a persistent model of your business — entities, products, customers, costs, contracts and how they relate — that keeps learning as your systems change. Dashboards and assistants can sit on top of it, and several do, but they are surfaces. The Brain is the memory underneath them, and it is the memory that makes an answer defensible.
SAP (ECC and S/4HANA), Oracle ERP (E-Business Suite and Fusion), Tally and Zoho are the four we are asked for most often, and they are where most Indian enterprise data actually sits. Beyond those: CRM and helpdesk platforms, warehouse, hospital, learning and point-of-sale systems, marketplace seller panels, and the WhatsApp threads, email and spreadsheets where a surprising amount of the real decision record lives. Whether a specific system can be read depends on the interfaces that vendor exposes. We assess your actual estate during the audit and say plainly which connections are straightforward, which need vendor cooperation, and which are not feasible.
It reads broadly and writes narrowly, and the two are configured separately. The default is read-only: the Brain observes, reasons and reports. Write access is enabled per workflow, with the scope, the approver and the audit trail agreed in writing first, and any consequential or irreversible action carries a named human checkpoint. The checkpoint is a setting you control rather than an assurance from us, and nothing is enabled because it was technically possible.
Agents are the hands; they are useful, increasingly commoditised, and only ever as good as the context someone hands them each time. The work moves and the memory does not. AG Brain is the memory — one context engine per client that learns what normal looks like for your business and lets every agent reason over connected truth rather than over a fresh prompt. That memory is what makes a gain attributable, an answer defensible, and the system worth more in month twelve than in month one.
Because you can trace it. Finance and operations arithmetic is computed deterministically, not generated — language models write the narrative and never the figure. Every number carries the source row it came from, and the model version that produced the narrative around it is recorded. If a figure cannot be traced to its source, it does not get published to you.
Each client runs in a dedicated, isolated environment. Data does not cross tenants and is not used to train any model outside yours. Hosting location is agreed in writing before deployment and stated in the contract; for Indian businesses that normally means infrastructure in India. Processor terms covering security, sub-processing, deletion, access logging and breach notification are part of the agreement rather than an annexure added later.
It is a fixed fee, quoted before it starts, with no variation once it is underway — the point of a fixed fee is that the diagnostic carries no risk you have to price. It is read-only: you send an export, nothing is installed, nothing in production is touched. At the end you get a department-by-department audit in ₹, the top three recoverable opportunities ranked with evidence, a fixed-fee deployment plan and your first morning brief generated from your own data. If you proceed, the audit fee is folded into month one. If you do not, the audit is yours to keep and act on without us.
The audit gives you a defensible number in ten days. A first production workflow — one department, one baseline, one morning brief — is typically the first milestone after that, with the timeline fixed in the deployment plan rather than estimated here. Further departments follow in waves. What we will not do is quote a go-live date before seeing your systems: integration, not software, is almost always the longest part of a deployment, and a date set before that is known is a date set to be missed.

One Brain. One memory. One briefing every morning.

Ten days, a fixed fee, nothing touched in production — and a number you can take to your board.

Book the 10-Day Signal Audit See CuraOS