Real-World Observations. On Demand.
Sentinel Watch connects enterprise clients with a vetted global network of human observers who watch, classify, and tag real-world events — live or scheduled — delivering structured training data your models can actually learn from.
What We Do
We operate a managed network of real-world observers — people in the field equipped with structured reporting tools. Enterprise clients define the events they care about; our network finds, documents, and delivers them as clean, labeled data.
The result: a scalable human-in-the-loop data pipeline that produces contextually rich, edge-case observations that synthetic data and traditional scraping cannot replicate.
Who Uses Sentinel Watch
AI & ML Teams
Generate rare-event and edge-case training data without synthetic shortcuts. Real humans, real environments, real labels — at the scale and specificity your models need.
Market Research Firms
Deploy observation tasks across locations and demographics. Know how customers actually behave in-store and in the wild — not just what they report in surveys.
Custom Programs
You define the taxonomy. We deploy the observers. Receive structured, timestamped, geolocated data tailored to your specific research question or model training objective.
Example Use Cases
- Vision model training — Observers tag specific real-world events your model needs to learn: product handling, crowd behaviors, safety incidents, or any custom event type you define.
- Retail & CPG research — Track whether customers read product labels, how they interact with shelf displays, or which packaging variants attract attention.
- Brand & field intelligence — Verify compliance, document in-store execution, or monitor how your product is presented across geographies.
- Behavioral & social research — Structured observation of public behaviors at scale, with consistent taxonomy and researcher-defined classification criteria.
- Infrastructure & logistics verification — Field confirmation of conditions, statuses, or events that remote sensors cannot reliably detect.
Why Sentinel Watch
✓ Human-verified observations — not crowdsourced noise. Every data point comes from a vetted observer following your classification protocol.
✓ Custom event taxonomies — you define what matters. We don’t impose a fixed schema; your research question shapes the data structure.
✓ Scalable deployment — regional pilots or global programs. Start with a focused geography and expand based on results.
✓ Structured output — timestamped, geolocated, and formatted for direct ingestion into your ML pipeline or analytics stack.
✓ Confidential by design — your research program, taxonomies, and data remain yours. We do not aggregate or resell client observation data.
✓ Pilot-first approach — we scope every new program as a defined pilot before scaling, so you can validate quality and fit before committing to volume.
Ready to Define Your First Observation Program?
Talk to us about your data needs. We’ll scope a pilot, walk you through our observer methodology, and show you what structured human observation data looks like in practice.