Ten disciplines covering everything from a first AI strategy to autonomous agents running your operations. Every one ends in production.
Autonomous agents that plan, decide, and act across your systems — with human oversight built in.
Grounded, on-brand conversational AI for support, sales, and internal knowledge.
Natural, low-latency voice AI for inbound support, outbound outreach, and reception.
AI-powered automation of document, data, and decision workflows.
End-to-end orchestration connecting AI, people, and systems into governed pipelines.
Native-quality iOS & Android apps with AI at the core of the experience.
Fast, elegant web products with AI-native UX — copilots, canvases, and dashboards.
Full-cycle development of AI SaaS products — from idea to paying customers.
Embed AI into the tools you already run — CRM, ERP, helpdesk, and data stack.
Executive-level AI strategy, roadmaps, and governance that survive contact with reality.
Decision guide
The three most-confused terms in enterprise AI, compared honestly. Most clients need a combination — discovery tells you which.
Use a chatbot when the answers already exist in your approved content and people keep asking for them. Use intelligent automation when structured data has to be extracted from unstructured documents and processed through fixed rules. Use an AI agent when the work requires assembling context from several systems, applying judgement that varies case by case, and then taking action. If any of those three conditions is missing, an agent will cost roughly ten times more per task than the simpler option and be harder to trust.
| Attribute | AI Chatbot | Intelligent Automation | AI Agent |
|---|---|---|---|
| What it is | Conversational AI that answers questions from your approved content | AI that reads, extracts, and processes documents and data flows | Goal-driven AI that plans steps, uses tools, and completes tasks |
| Best for | Support deflection, lead capture, internal knowledge | Invoices, claims, contracts, back-office processing | Multi-step operational work: exceptions, research, coordination |
| Human involvement | Escalates conversations it cannot resolve | Reviews low-confidence items in a queue | Approves high-impact actions at defined gates |
| Typical timeline | 4–6 weeks to first channel | 6–10 weeks to parallel run | 8–12 weeks to supervised autonomy |
| Example outcome | 62% ticket deflection in 90 days | Claims intake: 3 days → 4 hours | 73% of dispatch exceptions resolved autonomously |
Case studies
A result from each service line, with the client context that produced it.
73% of dispatch exceptions resolved autonomously
We deployed an exception-handling agent across 14 regional hubs. It reads shipment events, cross-checks carrier SLAs, and resolves or escalates each case — cutting average resolution time from 4 hours to 11 minutes.
A national logistics operator
62% ticket deflection in 90 days
Grounded on 4,000 support articles and order APIs, the assistant handles order status, returns, and troubleshooting — CSAT on bot-resolved tickets is 4.6/5.
A D2C electronics brand
31% more appointments booked
The voice agent answers every inbound call, checks real calendar availability, books and confirms appointments, and sends SMS reminders — recovering calls that previously hit voicemail.
A 40-location dental group
Claims intake time cut from 3 days to 4 hours
AI reads claim forms, medical reports, and photos; validates against policy data; and routes 88% of claims straight to adjudication with zero manual data entry.
A mid-market insurance carrier
9 languages shipped same-day instead of weekly
A governed pipeline chains transcription, translation, human review, and publishing — with per-step SLAs and automatic fallback between model providers.
A media localisation company
Inspection reports generated 12× faster
Inspectors photograph sites; on-device vision models tag defects offline, and a language model drafts the full report before they reach the car.
A field-inspection startup
Research time per matter down 58%
A streaming copilot with paragraph-level citations sits beside the document viewer; lawyers accept, edit, or trace every AI suggestion to its source.
A legal research platform
$40k MRR within 6 months of launch
We productized their screening expertise into a self-serve AI screening SaaS — multi-tenant, usage-billed, with a 71% gross margin on AI features.
A recruiting agency
2.1 hours saved per rep per day
AI call summaries, next-step drafting, and pipeline hygiene run natively inside Salesforce — no new tools, no copy-paste, full audit.
A 900-seat sales organisation
₹18 crore annual savings identified, 3 initiatives live in 6 months
A 6-week discovery across 5 plants produced a ranked portfolio of 14 AI opportunities; we then delivered the top three ourselves.
A PE-backed manufacturing group
Our discovery program scores every AI opportunity in your business by ROI and feasibility — in four weeks, fixed fee.
Book a discovery callThirty minutes, concrete answers, and an honest view on whether AI is the right tool for your problem.