Kweka

Trade-channel inventory and sell-through panel for distributor-reliant industries (agri inputs, FMCG, building materials): closing stock by distributor and location, primary sales (manufacturer to distributor) versus secondary sales (distributor to retailer, i.e. true offtake), inventory ageing and expiry risk, stock returns, SKU-level moving versus non-moving classification, and geo-mapped demand hotspots — assembled by AI extraction from distributors' own PDF, Excel and photographed reports rather than from a formal dealer management system.

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Coverage

Universe, instruments and categories.

Industry: Application Software
Instruments: equities
Categories: Supply ChainAlternativeFundamental
Regions: APAC
Sample tickers: HINDUNILVR.NSITC.NSTATACONSUM.NSUPL.NSGRASIM.NSAMBUJACEM.NS

Dataset card

Type: not stated
Format: Multimodal input (PDF, Excel, photographed documents) normalised into Tabular
Volume: Request further research — volume is undisclosed and equals nodes x cadence x SKUs. Scale check: one mid-size manufacturer channel (500 distributors x 500 SKUs x weekly stock reports) alone yields ~250K structured records per month, so the aggregate is bounded only by deployment count — the specific node and history numbers are the first question for the operator
Users: Not disclosed; B2B deployment count rather than registered users — est. tens of manufacturer deployments with hundreds to low thousands of reporting distributor nodes (inferred from a 3-person company selling a 3-4 week implementation B2B product)
History: 2 years
Update frequency: not stated
Growth: Active but early-stage (all six capabilities marked Active rather than roadmap, so the product is shipped and live; a 3-person team with no disclosed funding indicates a small early customer base rather than a scale-up)
Launched: est. 2023-2025 (the core capability is AI extraction from photographed and PDF distributor documents, which depends on document-AI models available only from 2023, and there is no funding history and only a 3-person team — consistent with a very recent founding)
Delivery: not stated
Entity mapping: not stated
Sample: not stated
Point-in-time: not stated
Licence: not stated

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