Presence
Detect when a shopper is nearby and whether an interaction should begin.
Multi-modal edge inferencing
AI staff need to understand the room
Physical retail is noisy, fast-moving, and full of ambiguous human signals. Biscuit's edge inferencing system gives AI agents real-time context about the shoppers in front of them, so they can engage naturally and respond intelligently.
Patent-pending edge perception technology
Biscuit reasons about presence, attention, engagement, and interaction state where the retail interaction is happening.
- Reasons about shoppers up to 100 times per second.
- Runs context-sensitive perception at the endpoint.
- Feeds cleaner context into the AI sales or service agent.
What the edge system understands
Attention
Reason about whether a shopper is engaged, waiting, browsing, or walking away.
Speech and interaction state
Combine speech signals with physical context so the agent can respond at the right time.
Session boundaries
Help the system understand when an interaction starts, continues, or ends.
Better perception creates better agents
Most AI systems rely on clean text input or a button press. Stores do not work that way. Biscuit's perception layer gives the agent cleaner context before it speaks, recommends, routes, or takes action.
- Less friction for shoppers
- Fewer false starts
- Better turn-taking
- Faster responses
- More useful analytics
- Stronger sales and service outcomes
Technical flow
The edge system turns noisy endpoint signals into interaction context the agent can use, then routes outcomes back into analytics and improvement loops.
- 1 Sensors and endpoint signals
- 2 On-device perception loop
- 3 Engagement and interaction state
- 4 Agent context
- 5 Sales or service action
- 6 Analytics and improvement loop
Deploy perception where the interaction happens
Edge inferencing helps AI staff understand shoppers without forcing every interaction through a fragile touchscreen-only path.