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Built for sectorswhere answerscarry weight.

The constraints differ by sector — languages, data rules, who has to sign off — so the systems do too. Here is how that plays out in the places we work.

Sector 01

Government & public sector

Searchable circulars and resolutions, citizen-facing assistants, and on-premise deployments where policy requires them.

Constraints

  • Years of formal documents in Marathi and English
  • Strict rules on where data may be processed
  • Offices with very different hardware

What we build

  • Circular and GR search with citations
  • Department knowledge assistants
  • On-premise and air-gapped deployments
Case study DemonstratedA searchable memory of government resolutions

Sector 02

Law enforcement

Air-gapped retrieval across orders, procedures and case material in English, Hindi and Marathi.

Constraints

  • Nothing can touch the internet
  • Three languages, often within one file
  • Officers need the exact source passage

What we build

  • Offline document intelligence
  • Procedure and order lookup
  • Single-GPU deployments
Case study DemonstratedOffline answers from 800 documents, in three languages

Sector 03

Healthcare

Patient assistants, enquiry triage and social care teams — with medical questions always routed to a clinician.

Constraints

  • Medical questions must never get an automated answer
  • Patients write in English and Marathi
  • Every reply carries the practice's name

What we build

  • Patient assistants grounded in clinician material
  • Comment and enquiry agents
  • Care-team dashboards with escalation
Case study DeliveredAn AI care team for a cardiology practice

Sector 04

Engineering & EPC

Proposal engineering, technology selection and budgetary costing, straight from CRM leads.

Constraints

  • Quotes are engineering decisions, not catalogue prices
  • Costs move 30% or more
  • Senior engineers are the bottleneck

What we build

  • Proposal and bid copilots
  • Costing engines
  • Section-level review loops
Case study DeliveredProposal engineering: two days down to hours

Sector 06

Real estate

Listing extraction from broker WhatsApp groups and follow-up on leads that went cold.

Constraints

  • Listings arrive as messy chat messages
  • Hindi and Marathi number words and local units
  • Leads go cold fast

What we build

  • Listing extraction pipelines
  • Lead follow-up voice agents
  • WhatsApp enquiry automation
Case study DeliveredBroker WhatsApp chatter, turned into a clean listings table

Sector 07

Retail & e-commerce

Customer support that resolves routine tickets, and AI modules that sit alongside retail ERP.

Constraints

  • High ticket volumes with repeat questions
  • Catalogue and order data spread across systems
  • Retailers who live on WhatsApp

What we build

  • Ticket-based AI customer support
  • WhatsApp retailer assistants
  • Onboarding and training assistants

Not on the list?

If the work is document-heavy, repetitive and costly, it is usually a fit.

Describe your process

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