Practice
Hyper-customised AI software
We do not drop a chatbot on your intranet and call it transformation. We build models and interfaces that know your SKUs, your SOPs, your languages, and your risk appetite.
Document intelligence
Operations copilots
Vision QC
Forecasting
Agent workflows
On-prem / VPC
What “hyper-custom” actually means
The model is the easy part. The hard part is retrieval over messy Hindi-English PDFs, tool-calling into Tally or SAP, and a UI a supervisor will trust at 2 a.m. We design that full loop.
- Fine-tunes or RAG over your corpus — not a public web average
- Deterministic rules layered over probabilistic models
- Audit trails for every suggestion that touches money, safety, or compliance
- Private deployment when data cannot leave your network
Typical AI programmes
| System | What it does | Signals of success |
|---|---|---|
| Contract & invoice intelligence | Extracts, checks GST, flags mismatches, drafts vendor queries. | Hours per batch, error rate vs. clerks. |
| Plant / warehouse copilot | Answers “why is dock 4 late?” from WMS, IoT, and shift notes. | Time-to-root-cause, supervisor adoption. |
| Visual quality | Camera + model on a specific defect family, not generic “AI vision”. | Escape rate, false rejects. |
| Demand & energy forecast | Fits your seasonality, holidays, and machine duty cycles. | MAPE vs. the spreadsheet you use today. |
| Agentic back-office | Multi-step workflows with human gates: credit notes, RMA, dispatch holds. | Cycle time, exception volume. |
Guardrails we insist on
Grounding
Answers cite sources. If the corpus is silent, the system says so.
Role and tenancy
A store manager never sees another franchise’s margins.
Eval harness
Golden questions from your SMEs, run on every model change.