Industries
Industry context decides the system.
- Sectors
- Eight, chosen for fit
- Principle
- Problem first, model second
- Data
- Private deployment where required
- Proof
- Measured against your baseline
I.01 · Banking · NBFCs · Lending · Insurance · Payments
Financial Services and FinTech
Scale customer operations without weakening control.
Lenders, insurers and payment companies run high-volume customer processes under close regulatory scrutiny. AI can add capacity in collections, onboarding and servicing — but only if every interaction and decision remains explainable and auditable.
Operational challenges
- Collections and servicing volumes that grow faster than contact-centre capacity
- Manual KYC, underwriting and claims document review
- Customer data fragmented across core systems, CRMs and channels
Where AI and software engineering apply
- Collections and servicing
- Voice and WhatsApp agents for payment reminders and promise-to-pay capture, with scripts, call windows and escalation set by your policy.
- Onboarding and KYC
- Extraction and verification of identity, income and business documents, with exceptions routed to reviewers.
- Underwriting support
- Summaries of applicant documents and bank statements for credit teams, with the source of every figure shown.
- Risk analytics
- Anomaly detection on transaction and operational data, surfaced to analysts rather than acted on automatically.
What we design for
- A complete audit trail for every automated interaction and decision
- Designed to support RBI requirements on digital lending, outsourcing and fair practices
- Private deployment where data cannot leave regulated infrastructure
I.02 · Hospitals · Clinics · Diagnostics · Digital health
Healthcare and HealthTech
Return clinical time to clinicians.
Providers lose capacity to scheduling, documentation and patient communication. AI can absorb much of that administrative load — provided patient data is protected and clinical judgement stays with clinicians.
Operational challenges
- Front-desk and call-centre load from appointments and report enquiries
- Clinical and claims documentation that consumes staff time
- Patient records spread across systems with limited interoperability
Where AI and software engineering apply
- Patient access
- Appointment booking, reminders and report-ready notifications over voice and WhatsApp.
- Documentation support
- Extraction and summarisation of records, prescriptions and discharge summaries, for review by clinical staff.
- Claims and revenue cycle
- Assembly and validation of documents for insurance claims and pre-authorisations.
- Staff knowledge
- Assistants that answer from protocols, SOPs and formularies, citing their source.
What we design for
- Consent and data handling consistent with the Digital Personal Data Protection Act, 2023
- Interoperability with Ayushman Bharat Digital Mission standards where relevant
- Clinical decisions remain with qualified professionals — AI assists, it does not diagnose
I.03 · Discrete · Process · Automotive · Industrial equipment
Manufacturing and Industrial Technology
Connect the plant floor to the decisions above it.
Manufacturers generate data in ERP, MES, quality systems and supplier documents, yet most decisions still depend on manual consolidation. AI and computer vision shorten that loop — and our Physical AI research aims, in time, to close it on the machines themselves.
Operational challenges
- Quality inspection that depends on manual visual checks
- Supplier certificates, drawings and purchase documents processed by hand
- Planning decisions assembled from ERP exports and spreadsheets
Where AI and software engineering apply
- Visual inspection
- Camera-based defect detection at inspection stations, with every image and decision logged for traceability.
- Supplier documentation
- Extraction and validation of certificates of analysis, drawings and purchase orders against specification.
- Planning assistance
- Natural-language access to ERP and production data for planners, with the underlying query shown.
- Maintenance intelligence
- Analysis of sensor and maintenance logs to prioritise inspections and reduce unplanned downtime.
What we design for
- Operation on edge hardware with intermittent connectivity
- Integration with existing ERP and MES, not replacement
- Safety-critical actions kept under independent, deterministic control
I.04 · D2C brands · Marketplaces · Omnichannel retail
Retail and E-commerce
Resolve every order conversation at the speed of checkout.
Digital commerce runs on thin margins and high volumes. Most customer contact concerns order status, delivery, payment confirmation and returns — work AI can resolve directly once it is connected to order and logistics systems.
Operational challenges
- Support volumes dominated by repetitive order and delivery queries
- Return-to-origin losses on unconfirmed cash-on-delivery orders
- Catalogue content that cannot keep pace with the assortment
Where AI and software engineering apply
- Order support
- WhatsApp and chat agents that resolve order, delivery and return queries from live system data.
- COD confirmation
- Automated order confirmation and address verification before dispatch.
- Catalogue intelligence
- Generation and enrichment of product titles, attributes and descriptions, with review workflows.
- Demand insight
- Forecasting and assortment analysis from sales, inventory and marketplace data.
What we design for
- Real-time integration with order, inventory and logistics platforms
- Use of the official WhatsApp Business Platform and approved templates
- Brand-consistent tone, with human escalation for complaints
I.05 · 3PL · Express · Freight · Field services
Logistics and Supply Chain
Turn status calls into proactive updates.
Logistics operators coordinate drivers, warehouses and customers across time-critical processes. Much of the operational load is communication and documentation — exactly where AI reduces cost and improves first-attempt delivery.
Operational challenges
- Inbound calls from customers and partners asking for shipment status
- Proof-of-delivery and trade documents processed manually
- Exceptions detected after the customer has already been affected
Where AI and software engineering apply
- Proactive communication
- Automated delivery updates and rescheduling over WhatsApp and voice.
- Document processing
- Extraction from proofs of delivery, e-way bills, invoices and customs documents.
- Exception management
- Alerts on delays and anomalies from tracking and telematics data, routed to the right team.
- Dispatch support
- Assistants for scheduling and assigning drivers and field technicians.
What we design for
- Integration with TMS, WMS and telematics providers
- High availability through peak volumes
- Operation in the languages drivers and customers actually speak
I.06 · B2B SaaS · Platforms · Technology companies
Enterprise Software and SaaS
Ship AI features your customers can trust.
Software companies are expected to add AI capabilities quickly while keeping quality, security and unit economics under control. That requires evaluation, guardrails and cost engineering alongside the features themselves.
Operational challenges
- Roadmap pressure to deliver AI features without a specialised team
- Uncertain quality and behaviour of LLM features in production
- Model costs that erode margins as usage grows
Where AI and software engineering apply
- In-product copilots
- Assistants, generation and search designed into your product experience.
- Agentic features
- Workflow automation inside your product, with permissions and audit logs your customers can review.
- Evaluation infrastructure
- Test suites and regression checks integrated into your CI/CD pipeline.
- Cost engineering
- Usage attribution per customer and feature, model routing and caching — the problem our TokenFin work addresses.
What we design for
- Multi-tenant data isolation that passes enterprise security reviews
- A model-provider abstraction that avoids lock-in
- Engineers who work inside your repositories, processes and release cycles
I.07 · Developers · Brokerages · Property management
Real Estate and PropTech
Respond to every enquiry while it is still warm.
Real estate businesses invest heavily in enquiries from portals and campaigns, then lose many of them to delayed follow-up. Construction and property management add a substantial documentation burden.
Operational challenges
- Portal and campaign leads contacted hours or days after the enquiry
- Site-visit scheduling and follow-up managed by hand
- Agreements, approvals and drawings reviewed manually
Where AI and software engineering apply
- Lead response
- Immediate call-back and qualification of portal leads by voice agents, with results written to the CRM.
- Visit scheduling
- Booking, reminders and rescheduling of site visits.
- Sales enablement
- An inventory, pricing and availability assistant for sales teams.
- Document review
- Extraction from agreements, approvals and tenancy documents.
What we design for
- Integration with property portals and real estate CRMs
- Compliance with consent and commercial-communication regulations
- Inventory and pricing that stay accurate and current
I.08 · Universities · Schools · Test preparation · EdTech
Education and EdTech
Convert admission-season demand into enrolments.
Institutions face sharp seasonal peaks in enquiries and a year-round need for student support. AI provides timely, consistent responses at scale, so counsellors can focus on the conversations that need them.
Operational challenges
- Admission enquiries that peak beyond counselling capacity
- Fee reminders and administrative queries handled manually
- Little personalised support for students between classes
Where AI and software engineering apply
- Admissions
- Enquiry response, counselling follow-up and demo-class scheduling over voice and WhatsApp.
- Student services
- Assistants for fees, timetables and administrative questions.
- Learning support
- Course assistants grounded strictly in approved curriculum material.
- Funnel analytics
- Analysis of the journey from first enquiry to enrolment.
What we design for
- Age-appropriate safeguards and parental consent where required
- Answers grounded only in approved material
- Integration with student information systems and CRMs
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