Industries & use cases

Real problems first.
AI second.

Start with what costs you time, money or customers. We shape intelligence around your industry, connect it to the work already happening, and measure what changes.

01 Start with the work

Model choice follows the operating problem.

02 Design for the rules

Controls and evidence are part of the system.

03 Stay accountable

Production ownership does not end at launch.

The business gap

AI adoption is rising.
Results need to follow.

Twelve familiar problems. Each begins with the work that needs to change, and a practical way forward.

01

Pilots that never reach production

"We ran three AI pilots last year. None of them are live today."

What we do

We assess your data, workflows and rules before building anything, so we only build what can actually go live. Then we deploy it and stay on until it works.

02

Impact no one can measure

"The board keeps asking what we got for the AI spend. We don't have an answer."

What we do

We agree the outcome with you up front, in business terms, and report against it every month. You pay for results, not a bundle of technology.

03

Data and tools that don't talk

"Our knowledge lives in email, WhatsApp, spreadsheets and people's heads."

What we do

We build inside the systems your teams already use: CRM, Teams, Webex, Zoom, WhatsApp, Google, Zoho. The AI connects your work instead of adding another app.

04

Risk, trust and compliance

"We can't let an AI act on customer data without knowing what it's doing."

What we do

Humans approve every key step. Every action is logged with a full audit trail, with guardrails designed for your regulatory environment.

05

Customers wait too long for answers

"Customers wait hours for answers our team has already given a hundred times."

What we do

AI agents answer on WhatsApp, web chat and phone, in English and Indian languages, day and night. Anything complex goes to a person with the full context.

06

Knowledge buried in documents

"The answer is somewhere in our files. Nobody can find it."

What we do

We make your policies, contracts, manuals and past work searchable in plain language, with every answer linked to its source.

07

Manual back-office work

"Our team spends days typing invoices and checking forms."

What we do

AI reads, checks and routes documents automatically. Your people only handle the exceptions, not every single page.

08

Decisions made too late

"We only find out something went wrong after the month closes."

What we do

AI watches your live data, forecasts what's coming and alerts the right person early, while there's still time to act.

09

Shadow AI no one can see

"Teams are using AI everywhere. We don't know which tools, what it costs, or what data goes in."

What we do

The Governance Console shows every team's AI spend, models and keys in one place. It flags sensitive data in prompts, unapproved models and spend with no records, every week.

10

Cameras that record but never decide

"We have hundreds of cameras. The footage just sits there until something goes wrong."

What we do

Video Intelligence reads identity, counts and condition from the cameras you already have, at night and in rain, fog or dust. Every event carries its frame into your ERP, maintenance or warehouse system.

11

No clear place to start

"Everyone says we need AI. Nobody can say where to start or what it's worth."

What we do

Our Readiness framework scores you on seven layers: leadership, data, technology, workforce, process, culture and governance. Start with a free 5-minute Pulse and see your weakest layer right away.

12

Leaders and teams see AI differently

"The leadership deck says we're ready. The people doing the work were never asked."

What we do

Leaders rate readiness, then staff answer the same questions anonymously. The gap between the two shows exactly where adoption will stall, before you spend on tools.

Find where we would start

Explore by industry

One operating model.
Different sector realities.

Choose a sector to see the problems we focus on, the guardrails that shape the build and the Purposive work most relevant to it.

Healthcare professionals reviewing a connected care workflow in a hospital
01 Healthcare

Connected care

Connect the care journey without losing clinical control.

Bring intake, triage, documentation, safety checks, pharmacy, diagnostics, follow-up and claims into one traceable workflow. The clinician remains the decision-maker; the system makes the record easier to use.

Deployment guardrails

CDSCO contextDPDP Act 2023ABDMHL7 / FHIR
View Healthcare in depth

Where we apply intelligence

Focused on the moments where action matters.

01

Clinical documentation at the point of care

02

Medication safety and prescribing support

03

Patient intake, triage and follow-up

04

Operational visibility from booking to claims

Industries & use cases

Start with the problem.
See what changes.

Explore our products and capabilities, then browse 105 practical applications across industries and business functions.

9 Purposive solutions · 105 library applications

Purposive products & capabilities

09

WOLM · Sales & Revenue

Sales teams lose context between every call

Problem
Call prep is manual, follow-ups slip, and account knowledge leaves when people do.
Process
WOLM runs the whole cycle inside your CRM: briefing before the call, help during it, and automatic follow-up after.
Outcome
Better-prepared reps, follow-ups that always happen, and knowledge that builds up instead of disappearing.

Viver · Healthcare

Missed appointments and slow clinical notes

Problem
Paper bookings, hand-typed notes with no safety check, and patient follow-up that rarely happens.
Process
WhatsApp registration, intake, triage and reminders, linked to real-time notes with clinician control and a full audit trail.
Outcome
Modelled target: OPD no-shows from about 30% toward under 12%, with audit-ready notes from booking to recovery.

Purposive Spaces · Real Estate

Living spaces run on disconnected tools

Problem
Co-living, PG and hostel operators juggle occupancy, resident requests and maintenance across separate tools.
Process
An agent layer coordinates occupancy, requests, maintenance and resident experience end to end.
Outcome
One coordinated operation, faster resolution, and happier residents.

Financial Services · AI Governance

Slow document checks and compliance reviews

Problem
Teams spend hours reading applications, KYC files and policy documents by hand, and every decision needs a clear record.
Process
AI reads and checks documents, flags gaps and risks, and drafts a summary. A named person makes the final call, and every step is logged.
Outcome
Faster turnaround, consistent checks, and decisions you can explain to an auditor or regulator.

Manufacturing & Supply Chain · Video Intelligence

Problems on the floor are spotted too late

Problem
Quality issues, safety risks and supply delays are found after the damage is done, often from a manual report.
Process
AI watches camera feeds and operational data, raises alerts in real time, and sends them to the right person to act.
Outcome
Issues caught early, less waste and downtime, and a clear record of what happened and who acted.

Professional Services · Purposive Agent

Expert time lost to repeat work

Problem
Proposals, research, meeting notes and status reports are rebuilt from scratch, project after project.
Process
Specialist agents draft, research and summarise from your past work and live meetings. Your experts review and approve.
Outcome
More time on client work, faster delivery, and quality that stays consistent across teams.

AI Readiness · Advisory

AI plans that break on the first weak layer

Problem
Companies buy AI tools before checking if their data, people and processes can use them. Pilots stall and nobody knows why.
Process
Score all seven layers, from a free 5-minute Pulse to a 90-minute Snapshot, a 2–3 week Audit or a 90-Day Sprint with one pilot live. Every option uses the same scale, so you can start small and go deeper.
Outcome
Your weakest layer named, the top three fixes in order, use cases ranked by value, and a score you can re-check every quarter.

Governance Console · AI Governance

AI use is growing faster than control

Problem
Every team uses different AI models and keys. Nobody sees the full bill, the risky data in prompts, or who owns what.
Process
The console reads usage records and provider bills, checks prompts for Indian personal data and secrets, and runs a weekly analysis. Findings go to the owning team with clear steps.
Outcome
One view of AI spend and risk, budgets that don't surprise you, and evidence mapped to DPDP, CERT-In, ISO/IEC 42001 and NIST AI RMF.

Video Intelligence Suite · Vision Intelligence

Cameras record everything and decide nothing

Problem
Footage sits in the video system until someone goes looking. Gate reads, counts and defect checks are still done by hand.
Process
Reads identity, geometry and condition from your existing RTSP/ONVIF cameras in one pass. Every event is logged with its frame and posted to ERP, CMMS, WMS or the control room.
Outcome
A structured, auditable record from every camera, with no new hardware. Runs at the edge, in your cloud or fully air-gapped, so footage stays in your perimeter.

Application library

Ideas to shape around your data, systems and priorities.

105
Banking & Finance

Real-time fraud detection

Fraud is spotted after the money has gone.

How it works

Scores every transaction as it happens and holds the suspicious ones for review.

Intended outcome

Fewer losses, fewer false alarms for genuine customers.

Banking & Finance

KYC and onboarding automation

Opening an account takes days of document checks.

How it works

Reads ID and address proofs, matches details and flags mismatches for a person to clear.

Intended outcome

Faster onboarding with a clean audit trail.

Banking & Finance

Credit underwriting assistant

Loan officers spend hours reading bank statements and financials.

How it works

Summarises the applicant's file, highlights risks and drafts the credit note.

Intended outcome

Quicker, more consistent lending decisions. A person still decides.

Banking & Finance

Collections that feel human

Generic reminders get ignored.

How it works

Sends the right reminder, in the right language, at the right time, and offers simple payment options.

Intended outcome

Better recovery with less pressure on the team.

Insurance

Claims intake and triage

Every claim waits in one long queue.

How it works

Reads photos and forms, checks the policy, and sorts simple claims from complex ones.

Intended outcome

Simple claims settle fast. Adjusters focus on the hard ones.

Insurance

Policy servicing assistant

Customers call to ask what their policy covers.

How it works

Answers coverage questions from the customer's actual policy, with the clause quoted.

Intended outcome

Fewer calls, clearer answers.

Healthcare

Ambient clinical notes

Doctors type notes long after the patient leaves.

How it works

Listens to the consultation (with consent) and drafts the note for the doctor to approve.

Intended outcome

More time with patients, less time typing.

Healthcare

Insurance pre-authorisation

Paperwork delays treatment and payment.

How it works

Pulls the right records, fills the forms and tracks approval status.

Intended outcome

Faster approvals, fewer rejected claims.

Healthcare

Discharge summaries and follow-up

Patients go home unsure what to do next.

How it works

Drafts clear discharge notes and sends medicine and check-up reminders on WhatsApp.

Intended outcome

Better recovery and fewer avoidable readmissions.

Retail & E-commerce

Personalised recommendations

Every shopper sees the same products.

How it works

Suggests products based on what each shopper browses and buys.

Intended outcome

Bigger baskets and more repeat customers.

Retail & E-commerce

Demand forecasting and restocking

Best-sellers run out while slow items pile up.

How it works

Forecasts demand by store and season and suggests what to reorder.

Intended outcome

Fewer stock-outs, less money stuck in inventory.

Retail & E-commerce

Product content at scale

Thousands of listings need titles, descriptions and translations.

How it works

Writes consistent product content in your brand voice and several languages.

Intended outcome

New products go live in hours, not weeks.

Showing 12 of 105 applications

Library applications describe possible uses and intended outcomes. Scope and results depend on the deployment. Smart-glasses concepts are prototypes.

Find your starting point

What needs to
work better?

Choose the situation closest to yours. See the approach, the first deliverables and the next step.

Where we would start

01

Start with an AI Readiness assessment

We check whether your data, workflows and rules can support the use case before anything is built.

  • Data and workflow map
  • Regulatory and risk check
  • A clear go-live timeline
Score your AI readiness

How we solve it

Assess to Success.
One accountable flow.

Five stages. A human decision at every handoff. The result stays in view from the first conversation to production.

  1. 01

    Discovery

    Assess

    Map your data, workflows and rules. Agree the result and the timeline.

    Human approval
  2. 02

    Architecture

    Design

    Shape the system around the problem, with clear human approval points.

    Human approval
  3. 03

    Engineering

    Build

    Build on your data and test with the people who will use it.

    Human approval
  4. 04

    Go-live

    Deploy

    Roll out with your team, monitor the transition and own the fixes.

    Human approval
  5. 05

    Measurement

    Success

    Report against the agreed result and keep improving.

    Human approval
See the Purposive agent flow

What stays constant

Sector-specific by design.
Accountable by default.

The interface changes. The data model changes. The rules change. Our standard for traceability, human control and production ownership does not.

01

Workflow first

We map the decision, the hand-offs and the systems around it before designing an agent.

02

Controls in the build

Access, escalation, evidence and human approval are architecture, not a policy added later.

03

Measured in production

We monitor whether the system is useful, safe and still earning its place after go-live.

Start with your operating reality

Bring us the workflow that matters.

We will help you decide what should be automated, what must stay human and what evidence production needs to keep.

Talk to us