No named owner
The project stalls exactly where the last one did — with no one accountable for the outcome.
AI Workflow Automation
Your bots handle the clicks. The judgment calls still land in someone's inbox.
Banao builds the orchestration and AI decision layer that finishes the process your RPA stops on — reading the input, making the call, escalating only the exceptions that are genuinely exceptions.
No new bots to babysit. The judgment layer runs on the automation you already have.
02 · What We Build
An automated process needs an orchestration engine and AI decision steps — not another bot.
The gap between a bot that clicks and a process that finishes is judgment. Ten pieces close it, layered on top of the automation you already have.
10
Components in every build
01
Orchestration Engine
Sequences every step across your systems, retries what fails, hands off only what's ready.
02
AI Decision Layer
Reads the input a bot can't parse and makes the call a rule can't encode.
03
Confidence Thresholds
Every AI decision carries a score. Above the line it runs. Below it, a person sees it.
04
Exception Design
A named path for every edge case — nothing falls through to a silent failure.
05
RPA Integration
Layers over the bots you've already built. Nothing gets ripped out to make room.
06
Audit Trail
Every input, decision and override logged — reconstructable after the fact.
07
System Integrations
Connects the ERPs, CRMs and ticketing tools the process already runs through.
08
Human-in-the-Loop Gates
Reviewers see the full context behind a flagged case, not just the flag.
09
Monitoring & Alerting
Live visibility into throughput and the exact step where a process is stuck.
10
Single Process Owner
One team accountable end to end — never a bot per task with no owner.
03 · RPA VS AI WORKFLOW AUTOMATION
RPA
AI
YOU
Show us where your process stalls
Three things stay true when AI joins your RPA.
Adding an AI decision layer changes what happens to the judgment calls your bots hand off. It doesn't change who owns the system, what your existing automation does, or where the record of a decision lives.
What stays exactly as it is
- The same rule-based steps, running on the same schedule
- Every bot you've already built and paid for, untouched
What gets added on top
- Judgment on the input your RPA can't parse, with a confidence score attached
- Escalation to a person only when that score falls below the line
What you keep
- Ownership of the system — no lock-in to Banao to keep it running
- The audit trail behind every decision it makes, on record
04 · How We Build
Book a Discovery Sprint →
Where automation usually stops — and the two layers we add on top of it.
Where it stops
01
Bots handle the clicks
RPA moves data between systems reliably — until the input needs a judgment call.
02
The judgment call lands in an inbox
No orchestration layer to route it, no owner assigned — it waits for a person to notice.
What we build on top
03
AI decision layer
The model reads the input and makes the call, with a confidence score attached to every decision.
04
Human gate
Below-threshold and exception cases route to a person with full context. Every call logged for audit.
05 · Why workflow-automation projects stall
Most automation work stalls at sixty percent — here's the pattern.
We get called in after the bots are live and the exceptions have taken over. Four reasons it happens. None of them are about the model.
60%
is where most initiatives plateau, bots live and exceptions unhandled.
01
Automating chaos
The process was inconsistent before automation touched it. A bot just runs the inconsistency faster.
02
No exception plan
Every process throws exceptions. Without a plan for handling them, they pile into someone's inbox.
03
A bot per task, no owner
Stitched together task by task, with nobody accountable end to end.
04
No measurement
Nobody tracked what "working" meant, so the plateau went unnoticed.
06 · Receipts
Live at three kinds of company.
An energy major, an enterprise services firm, and our own 300-person operation — the same decision layer, running in production, right now.
Indian Oil
Energy · Enterprise deploymentAI workflow automation deployed into an existing operating environment, running in production.
Anonymized B2B services firm
Services · Live, not a pilotClient identity withheld at their request. The workflow is in daily use, not a sandboxed proof of concept.
Banao — our own operation
Internal · ~300 seats · DailyInterviewGod, Vikaas and Vidya run hiring, outreach and upskilling for our own 300-person company on this same layer.
08 · Where We Deliver
Five offices. Four data-protection regimes. Compliance built in, not bolted on.
Every engagement runs under the regulatory regime of the market it serves — not one default policy stretched across geographies.
Bengaluru
India · DPDP Act
Engineering and delivery hub. Client data handled under India's Digital Personal Data Protection Act.
Chandigarh
India · DPDP Act
Engineering and delivery hub. Client data handled under India's Digital Personal Data Protection Act.
Dubai
UAE · PDPL
Regional hub for GCC engagements. Client data handled under the UAE's Personal Data Protection Law.
Cambridge
UK · UK GDPR
Regional hub for UK engagements. Client data handled under UK GDPR.
California
US · SOC 2
Regional hub for US engagements. Delivery controls audited to SOC 2.
09 · THE HONEST VERSION
01
02
03
04
05
Five cards. Four are reasons we'd say no.
We'd rather lose the deal in this section than six weeks into delivery.
Pilot, not production
We build systems that run against real data from day one. A demo with no deployment plan isn't in scope.
Happy path only
Automating the easy part and leaving the exceptions in an inbox is the plateau we're brought in to fix, not repeat.
No system access
We build inside your stack. Without scoped access to the systems the process touches, we can't ship in weeks.
Ready to ship
An owner in the room, real data, and a green light on access — that's what moves a proposal in one meeting.
Recognize card five?
Book a Discovery Sprint
10 · How We Start
Three steps. No slide deck at the end.
Bring one process — the one where the bots stop and a person starts deciding. We map it live, then you leave with a scoped, priced build plan.
01
Bring the process
The one place automation already stalls — an inbox full of exceptions, a step nobody automated because it needed judgment.
02
We map it with you
An engineer walks the exact decision points live — where a confidence threshold sits, where a human stays in the loop.
03
You get a build plan
Scoped, priced, and owned by you — a working plan for what ships and when, not a slide deck.
13 · GET STARTED
300-personoperation run on our own AI, every working day
30+clients live in production
2016building production AI, not pilots
This is the same judgment layer we run ourselves. Bring us the process it's missing from.
InterviewGod, Vikaas and Vidya run on it internally before any client does. See it on the process where your automation stops.
Book a Discovery Sprint →