TraceBoard Suite is three connected products — engineering items, controlled documentation, and verification — with standards-aware templates and assessments for teams working in regulated contexts. Here's what sets it apart from a disconnected spreadsheet workflow or heavyweight ALM rollout.
Engineering State is a deterministic, on-demand aggregate across compliance assessment, traceability, verification, risk, consistency, change impact and baseline readiness. It is calculated from recorded engineering facts and defined thresholds—not an AI opinion, certification score or release approval.
Review the dimensions behind the aggregate rather than relying on a generic project-health label.
Traceability, results, assessments, risks, consistency findings, change impact and baseline checks remain inspectable.
Everything below is a direct response to how regulated engineering teams actually work — not a generic feature list.
Standards-aware templates and assessments help teams organize engineering evidence for ISO 26262, IEC 62304, and DO-178C work. They support engineering review; they do not certify a product or replace a qualified compliance process.
Run the core suite on your own infrastructure, with local model support when configured. OIDC, remote Git and cloud LLMs remain optional network-dependent integrations.
One annual price per team size. No per-seat licensing that grows unpredictably as your project — or your headcount — does.
Requirements to tasks, tests, bugs, and documents — with suspect-link flagging when an upstream edit makes a downstream link stale.
Use supported JSON, CSV, XLSX, PDF, DOCX and Markdown operations for the workflows each endpoint implements. The site does not promise ReqIF or arbitrary full-fidelity interchange.
AI-cited artifact IDs and generated content are checked against available project data where supported, then remain subject to human review. The system does not guarantee semantic correctness.
TraceBoard Suite provides standards-aware analysis, templates, assessments, evidence and provenance for engineering review and audit preparation. It does not certify a product or determine that a customer is compliant.
Use them together, or start with just one. Shared project and item references connect the suite while each product handles its own operational work. The implementation supports baselines, evidence, tests, documents and traceability across the suite.
Enterprise requirements tools rarely lose on the license line. They lose on implementation consultants, ongoing admin overhead, and the months it takes before a team traces its first requirement.
TraceBoard ships with standards-aware engineering structure and evidence workflows; the speed-to-value trade-off is measured in less configuration, not a promise of compliance.
Configure AI through a supported local or OpenAI-compatible endpoint, and use the data operations implemented for each workflow.
AI can use a local Ollama or OpenAI-compatible HTTP endpoint. The behavior and quality of generated output depend on the selected model and its configuration.
Smaller models (≤7B) may produce less detailed narratives, while larger models provide deeper insights — giving you full control over the trade-off between cost, latency, and quality.
Your project remains on customer-controlled infrastructure, with supported endpoint-specific data operations rather than a promise of arbitrary interchange.
The fastest way to evaluate TraceBoard is against a real project — a messy spreadsheet, a spreadsheet or document you're tired of formatting by hand. Exact import and export support depends on the implemented operation; ReqIF is not supported.