Platform features
Unlock the full potential of AI-powered recommendations
Discover the core platform capabilities behind fast launches, richer control, and personalisation that keeps adapting as user behaviour changes.
Feature system
Shaped around delivery, control, and model intelligence
Browse the platform as an operator would: what gets you live fast, what keeps the system governed, and what improves model quality over time.
AWS-managed infrastructure, async jobs, and smart caching keep experiences responsive as demand spikes.
Push catalog items and events through ready-made REST endpoints and console toggles to get started fast.
Platform
Operate personalisation from one control plane
NeuronSearchLab unifies catalog ingestion, event capture, and model oversight so teams can curate tenant-specific experiences without wrangling bespoke infrastructure.
Realtime learning
Event ingestion lands within seconds and each request recomputes embeddings with the latest contextual filters.
Privacy-first
Tenant-scoped credentials, OAuth client controls, and role-aware teams keep access limited to the right people.
Unified signals
Catalog items, user activity, and business rules converge into a shared embeddings store with built-in usage analytics.
Experiments
Coordinate rollout guardrails and targeting rules from the console before promoting updates live.
What you get
Features built for personalization operators
NeuronSearchLab unifies data ingestion, context design, and release governance so product, growth, and engineering teams can steer recommendations without wrangling infrastructure.
Trigger tenant-specific training runs, review version metadata, and bake contextual guardrails into every release without swapping tools.
Bring catalog attributes, behavioural events, and guardrail logic into one signal layer with usage analytics baked in.
Issue, rotate, and revoke API keys or OAuth clients while keeping tenant boundaries tight-no infrastructure tickets required.
Stream events in seconds, recompute embeddings per request, and kick off retraining runs when behaviour shifts.
Push catalog entities and events through ready-made APIs, validate payloads in the console, and track training progress as you ramp.
Prepare guardrails, targeting rules, and approvals before any model goes live, all within the same workspace.
