FactoryLens · Natural-language intelligence over factory video
Ask your factory a question, get a grounded, timestamped, video-cited answer.
Safety unlocks the budget. Operations justifies the renewal. Natural language is the wedge.
8 people, all in hi-vis vests, 0 wearing hard-hats - headwear is caps/beanies only.
The thesis
Every factory runs cameras. Almost none of that footage is queryable.
A plant manager who wants to know how many times someone entered the press cell without a lockout last week has two options today: scrub hours of footage by hand, or buy a rigid detector that answers only the one question it was pre-configured for.
FactoryLens turns the camera estate into a question-answering surface: ask a question in plain language, get a grounded answer with clip citations. No detector to configure.
Why now
Three tailwinds converging in 2026
The market is large and compounding
Computer vision in manufacturing is ~$7.9B in 2026 at 12.7% CAGR to ~$16.2B by 2032. Edge deployment is already ~47% of CV spend and the fastest-growing slice.
The category leader vacated the field
Drishti, the reference brand in manufacturing video analytics, was acquired by Apple in September 2023 and is no longer sellable. Demand is stranded.
The interface paradigm shifted
Video foundation models (Twelve Labs Marengo 3.0 + Pegasus, on Amazon Bedrock as of Dec 2025) made natural-language video retrieval production-viable. Factory-safety incumbents still ship dashboards and alerts.
Market opportunity
Sizing the bet
Manufacturing is the largest CV vertical (~28% of CV spend) and edge deployment leads at ~47% share and the highest growth. That validates an edge-first architecture, not cloud-streaming.
The AI workplace-safety niche is small (~$122M) but sits inside a $26B+ safety budget growing 17%. The play is not to fight for the niche; it is to expand what video can do and pull from the larger safety + operations budgets.
- Third-party estimate
Market sizes: directional 2026 figures (Research and Markets, Mordor Intelligence, Genetec/Intellisee) - for sizing, not precise claims.
- Publicly reported
Drishti → Apple (Sept 2023) and Twelve Labs Marengo 3.0 + Pegasus on Amazon Bedrock (Dec 2025); competitor funding from public trackers.
- Incumbent-reported, not our data
The ~77% injury-reduction / ~$1.1M-per-site ROI anchors are Voxel/Intenseye-class incumbent results - FactoryLens has no pilot data.
- Measured live in this demo
Answer faithfulness is no longer just a target: the live demo ships a working evals rubric that measures it per answer.
The structural whitespace
One empty quadrant. That's the whole thesis.
Everyone makes you configure alerts on a safety-only tool, or offers open query with no factory depth. FactoryLens is alone in the manufacturing-native, ask-anything corner - the quadrant Drishti vacated.
Competitive landscape
Everyone makes you configure. No one lets you ask.
Voxel
Safety visionIntenseye
Safety visionProtex AI
Safety visionCompScience
Safety + insuranceTwelve Labs
Video foundation modelInvisible AI / Retrocausal
Mfg ops analyticsRockwell VisionAI (Elementary)
Industrial automationDrishti
Mfg video analyticsOur defensible wedge
Four moats, compounding
Interaction moat
Natural-language query becomes the daily habit; dashboards become a feature, not the product.
Domain moat
A manufacturing event ontology (PPE, LOTO, zone breach, forklift proximity, spill, cycle complete, micro-stoppage, idle, ergonomic strain) horizontal VLMs do not have.
Trust moat
Edge-first + privacy-by-design + an evals layer that makes answers auditable. This clears a works council and an EU AI Act review.
Wedge economics
Safety opens the door on existing budget; operations proves hard-dollar ROI that drives the renewal and the expansion.