TaskSense is an event-driven scheduling, automation, and execution platform built for distributed systems, manufacturing, infrastructure operations, and mission-critical enterprise workflows. One platform — schedule, run, monitor, audit.
Production-grade. Multi-tenant. Sub-millisecond pickup latency. Horizontally scalable runner fleet. Audit-trailed by default.
Schedule, distribute, coordinate, integrate, observe, predict, and secure — every capability your operations team needs, designed to compose rather than collide.
Express any pattern from one-time fires to deeply recurring rules — no Cron PhD required.
A self-registering runner fleet that scales horizontally and survives pod churn.
Coordinate access to physical equipment, devices, and shared resources across the fleet.
First-class connectors for the protocols your platform teams already speak.
Real-time signal from the platform itself — not bolted on, baked in.
Where the platform is heading — the data foundation is already in place.
Enterprise authentication, authorization, and trail — required by default, not an upgrade.
Microservices architecture, event-driven communication, dynamic registration, horizontal scale-out — TaskSense behaves like the systems it orchestrates.
TaskSense is deliberately domain-agnostic. Every task self-registers with a JSON schema describing what it needs to run; the scheduler UI renders pickers directly from those schemas; runners pick up work over Kafka or Solace; results stream back through correlation-tagged events.
The control plane is built from independently scalable microservices (scheduler, runner-registry, audit, mail, userdata, authentication, config) communicating over Kafka with an explicit topic contract per concern. State persists to MySQL; logs stream to MinIO. Every service emits monitoring + audit events without opt-in.
What happens when a schedule fires, traced end-to-end. Every step is observable, recoverable, and recorded.
Cron tick, external trigger, or workflow chain step. Topic-routed via Kafka.
Scheduler validates the task definition + payload against the registered schema.
Required equipment / locks / shared resources reserved before dispatch.
Distributed across the runner fleet; correlation ID + execution ID stamped.
Live log capture into MinIO; metrics streamed; UI gets server-sent events.
Completion / failure / suspend events fan out to subscribers + workflow chains.
Immutable audit record with before/after entity state and executing user.
Designed against the patterns manufacturing, infrastructure, and large enterprise teams hit in production every day. Plus open to specialised domains where the same schedule + runner + audit shape applies.
Recurring back-office jobs — reports, reconciliations, syncs — with full timezone, weekday, and time-window control.
Equipment reservation, recipe execution, batch coordination across shop-floor systems with shared-resource locking.
Patch windows, certificate rotation, backup orchestration across environments — with continuation modes for long-running work.
Probe-then-act runbooks, self-healing automations triggered by alerts, with audit-trailed runbook history.
Run inference jobs, retraining pipelines, model evaluation on a schedule with resource-aware GPU coordination.
The runner-SPI + protocol-connector model also fits network-element provisioning, config audits, and polling workflows for teams with that domain need.
Horizontal at every layer. Multi-node from day one. Tested under load.
Authentication, authorization, audit, and isolation are required by default — not premium add-ons.
RSA-key-rotated tokens, server-side blacklist propagation, OAuth2 client-credentials for service-to-service.
Granular SCHEDULE_CREATE / RUNNER_VIEW / AUDIT_EXPORT codes — never coarse "admin" roles.
Every state-mutating action recorded with before/after JSON snapshot, executing user, and request context.
Client-scoped data at every layer — schedules, audit, user data — isolated by tenant from query plan to UI.
No exotic frameworks. JVM-grade tooling that runs in every enterprise data centre.
Every screen is built from the schema — no per-task UI work.
TaskSense is in production today on the Nucleus platform stack. Public pricing lands when the managed control plane ships. Get on the early-access list and we will reach out personally.
Direct line to the architect. Hands-on onboarding. Founder pricing locked in.
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