Platforms

nSpace platforms demonstrate repeatable architecture patterns for data-intensive decision systems and AI-enabled software delivery. Each system shows a different application of the same core capability: ingest complex data, structure it for analysis, model uncertainty, expose intelligence through APIs and dashboards, and make software delivery more controlled and verifiable.

ForecastIQ

Forecasting and planning infrastructure for uncertain operational environments.

ForecastIQ demonstrates nSpace’s ability to build planning and forecasting systems that combine structured data pipelines, modeling workflows, scenario analysis, analytics APIs, and decision dashboards.

Demonstrates:

  • Forecasting system architecture
  • Model-ready data pipelines
  • Feature preparation
  • Planning workflows
  • Analytics-backed decision support
  • Production application delivery

Stage: Production / active platform.

BookieMonster

Market intelligence and probabilistic decision analytics.

BookieMonster is a data-intensive analytics platform that combines external APIs, historical data, probabilistic modeling, calibration, ranking logic, serving APIs, and operator dashboards.

The domain is sports markets, but the architecture pattern applies broadly: ingest volatile external signals, normalize large datasets, model uncertainty, rank opportunities, and present decision-ready intelligence to operators.

Demonstrates:

  • Large-scale external data ingestion
  • Historical and intraday analytics
  • Probabilistic modeling
  • Market movement analysis
  • Ranked decision workflows
  • API-backed dashboards

Stage: Active internal platform.

Abracapocus

Architecture-led agentic software delivery.

Abracapocus is nSpace’s AI-assisted software delivery orchestration system. It coordinates planning, task definition, agent execution, review, verification, retry decisions, and execution evidence so AI-assisted development can produce real software changes under architectural control.

Demonstrates:

  • Agentic development orchestration
  • Architecture-aware task planning
  • Controlled execution by AI coding agents
  • Review and verification gates
  • Repeatable delivery workflows
  • Evidence-based progress tracking

Stage: Active development / internal platform.