Feedback backlog. Report pileup. Documents in three languages. We build the system that clears it.
Six NLP capabilities — sentiment, summarization, multilingual processing, entity extraction — matched to the exact text workload slowing your team down. Delivered in weeks.
Book a Discovery Sprint →The first call is free · 45 minutes · no obligation
Text comes in messy. It leaves this pipeline structured.
One input path, four capabilities, one output your systems can use — not four separate vendors to stitch together.
Feedback, reports, contracts, and tickets — in whatever language they arrive in
Sentiment Analysis
Sentiment trends from feedback, tickets, and reviews.
Summarization
Reports and contracts condensed to what matters.
Multilingual AI
One pipeline across languages, not several.
Entity Extraction
Names, dates, amounts, and clauses, structured.
Structured, queryable text — ready for the system that acts on it next
Six steps. Nothing skipped.
Each stage is a checkpoint you can question before the next one starts — not a status update after the fact.
We map the exact text volume, formats, and languages moving through your team today — before proposing anything.
Checkpoint: sign off the workload map
Source systems, PII handling, and residency requirements are confirmed before a line of code is written.
Checkpoint: confirm data boundaries
Sentiment, summarization, multilingual, or entity extraction — matched to the workload, not defaulted to one stack.
Checkpoint: approve the approach
The system is built and tuned on your documents, not a benchmark dataset that has nothing to do with your text.
Checkpoint: review interim output
Outputs are checked against a held-out sample by your team, not just ours, before anything is called done.
Checkpoint: your team signs off accuracy
Shipped into your environment, documented, and owned by you — not licensed back to us.
Checkpoint: you hold the keysWhat we've shipped into production
Our production track record today: agentic AI and reinforcement-learning systems — an inventory system and a trading system, both live, both built through the same six-step process we run every engagement through.
NLP work — sentiment, summarization, multilingual, entity extraction — is entering that same pipeline now, inspected at the same checkpoints before anything ships.
DOGFOODED, NOT DEMOEDThe same discipline runs our own ~300-person operation: InterviewGod for hiring, Vikaas for outreach, Vidya for upskilling.
- Swiggy
- Myntra
- PhonePe
- Times Internet
- Indian Oil
- HCL
- CP Plus
- RAK Ceramics
- FootLocker
- Majra
We do not sell you software we hope works. We sell you the software we depend on.
Our production references today are agentic AI and RL systems, built for enterprise teams like these. NLP engagements are entering the same delivery pipeline now.
Before you book, the questions we'd ask too.
Straight answers on evidence, timeline, ownership, and who is actually building this.
Talk to us before you commit →
01You haven't shipped an NLP case study yet — why go first with you?
We run our own hiring, outreach, and training systems — InterviewGod, Vikaas, Vidya — on the same AI discipline we're proposing here, across a ~300-person operation. This engagement follows the identical six-step process already running 30+ client deployments, including Swiggy, Myntra, PhonePe, and Indian Oil.
02How long before this is actually running?
Weeks, not quarters. Each of the six delivery steps is a checkpoint — you see and question the system at every stage, not only at handoff.
03Do we get locked into your platform?
No. You own the system that gets built — that principle applies to every engagement, text-AI included, with no exceptions carved out.
04What if it doesn't fit our workload once we're inside it?
Sentiment, summarization, multilingual handling, and entity extraction are scoped against your actual backlog before build starts — the six-step process is built to be interrogated stage by stage, not accepted on faith.
05Who's on the team — in-house or outsourced?
In-house, across Bengaluru, Chandigarh, Dubai, Cambridge, and California — the same team that has been building since 2016.