IndiVillage

Services

AI that works in production. The whole programme, or just the piece you need.

Most of our largest customers buy one service. Some buy the full programme. The four below are modular — pick the entry-point that matches where you are now, sequence them when it makes sense.

IndiVillage service stack: data flows in, four service layers process it, results flow back out with your brand on the output
IndiVillage strategy meeting with client team around a table
01 ·
Data Consultancy
Start here if you have raw data but no labelling plan.
Define what 'good' looks like before annotation starts. Schema, taxonomy, QA framework and accuracy targets — set by people who have labelled 500M+ datapoints.
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IndiVillage operations floor annotation programme in progress
02 ·
Data Enrichment
Start here if you have a labelling plan but need volume.
Production-grade annotation at 99%+ accuracy. Image, video, LiDAR, text, audio — the same accuracy whether the volume is 10K or 10M.
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IndiVillage ML specialists reviewing model output at workstation
03 ·
Algorithm Development
Start here if you have labelled data but no model.
Build the model. Architecture, training, evaluation against your accuracy targets — on the Machani Group production stack, owned by your team at handover.
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Production dashboard showing model validation and performance metrics
04 ·
Deployment & Maintenance
Start here if your model works but drift is killing it.
Run it in production. Drift monitoring, retraining cycles, SLA-governed accuracy — because the world the model meets is not the world it was trained on.
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Next steps.

The 100-frame audit is a free 48-hour benchmark. You upload samples from your current pipeline; we return an accuracy, coverage and bias report — plus a service recommendation if useful. No sales conversation required.

Run a free auditTalk to a delivery lead →