CognitiveSDD
Phase-gated workflow orchestrator that walks AI agents through software projects (Python, TypeScript, C/C++) and engineering projects (SysML v2 MBSE) inside firewalled containers.
Development
Engineering tools for spec-driven development (SDD), predictive modelling, optimisation and active learning.
Spec-driven development frames AI agents with verifiable specifications; predictive modelling, optimisation and active learning cut the simulations and tests needed to converge. CognitiveSand turns both into concrete tools for software projects and Model-Based Systems Engineering.
Software products
Explore our specialized tools for systems engineering and automated predictive modeling.
CognitiveEstimator
Turn tabular in-memory data tables into calibrated, deterministic, dict-in/dict-out predictors.
Need AI that can be audited?
CognitiveSand can build the harness around the model so the output is traceable and integrated into your workflow.
CognitiveSDD: From requirements to verified artefacts
CognitiveSDD is a specs-driven workflow orchestrator that walks AI coding agents and AI modelling agents through phase-gated projects — from user stories or system needs to verified, traceable artefacts — inside network-firewalled containers. A single workflow engine, INCOSE-compliant requirements discipline, ADR-backed architecture, end-to-end @req / @story traceability, and a defense-in-depth security model apply to both project categories.
Software Projects (Python, TypeScript, C/C++, Go, Rust)
For software developers, CognitiveSDD orchestrates a structured workflow through user story discovery, requirements derivation, architecture design with ADRs, test specification with traceability markers, autonomous implementation inside firewalled containers, and full verification — producing source code, automated test suites, and a traceable build where every test links back to its requirement.
Engineering Projects (SysML v2 MBSE)
For systems engineers, CognitiveSDD applies the same phase-gated discipline to Model-Based Systems Engineering. The orchestrator guides the AI through stakeholder needs elicitation, INCOSE-compliant requirements, structural architecture, verification specs, and behavioural modelling — producing a complete SysML v2 model with end-to-end requirement-to-verification traceability.
CognitiveEstimator: Automated predictive modeling
CognitiveEstimator is our specialized tabular regression and probability calibration library designed for applied engineering. It turns tabular in-memory data tables (such as simulation runs, time-series data, or cost parameters) into calibrated, deterministic, dict-in/dict-out predictors under a strict execution budget, providing honest conformal uncertainty intervals and bit-identical reproducibility.