The operating system for engineering outcomes
Engineering is now measurable.
Binomial transforms code, pull requests, tickets, delivery workflows, and AI-assisted engineering activity into a financial and operational model of engineering performance.
For CTOs, CFOs, and operators who need more than dashboards, anecdotes, and lagging indicators.
Built for leadership teams managing modern, AI-assisted engineering organizations.
Connects to GitHub and Jira
Models risk, cost, quality, throughput, and control
Measures AI-driven engineering behavior and expense
Built for executive decision-making
AI Economics
AI is changing how software gets built. Binomial measures whether it is making engineering better.
Modern engineering organizations are increasingly AI-assisted. Binomial helps leadership understand what AI tooling costs, where it is being used, whether it is increasing throughput, and where it may be introducing churn, fragility, or risk.
Track AI tooling and inference cost across teams, repos, and workflows.
Measure actual usage patterns, not vanity rollout metrics.
Compare AI-driven engineering activity against throughput, review burden, rework, and delivery outcomes.
Identify where AI-generated code is increasing duplication, hallucinated logic, weak testing, or architectural drift.
System framing
Most organizations instrument engineering. Very few model it.
Engineering is now one of the largest drivers of cost, speed, execution risk, and operational complexity in modern companies. Yet most leadership teams still manage it through fragmented tools, lagging metrics, and intuition. Binomial creates a unified model of how engineering actually performs, including the growing financial and operational impact of AI-assisted development.
Code Intelligence
See how software quality, architecture, and AI-generated patterns affect the business.
Analyze pull requests, code quality, architecture drift, security exposure, and AI-generated code risk.
Workflow Intelligence
Connect ticketing and delivery systems to reveal drag, churn, delay, and execution friction.
Financial Intelligence
Quantify remediation cost, technical debt concentration, engineering inefficiency, and AI tooling expense in executive terms.
Governance Intelligence
Measure standards drift, compliance posture, ownership fragility, and policy adherence before they become systemic problems.
Outcome pillars
The metrics that matter are not buried in tooling.
Surface architectural, security, delivery, compliance, and AI-generated code exposure before it compounds.
Translate technical drag, code decay, and engineering inefficiency into quantified financial impact.
Measure how work actually moves through the system, not how teams describe it.
Turn standards, governance, and operating expectations into enforceable mechanisms.
Understand where AI is creating leverage, where it is adding cost, and where it is increasing operational risk.
Product modules
One platform. Multiple lenses.
Binomial Evaluate
Deep analysis where engineering work is created.
Deep analysis across pull requests, code quality, architecture, security, compliance, and AI-generated patterns.
Binomial Model
The living system underneath the metrics.
A living model of engineering performance built from source control, workflow, and delivery telemetry.
Binomial Policy
Governance that is active, inspectable, and enforceable.
Codify standards, governance, and compliance expectations into active enforcement.
Binomial Cost
Translate engineering drag into leadership visibility.
Translate remediation effort, technical drag, engineering inefficiency, and budget priorities into leadership visibility.
Binomial AI Economics
Distinguish real AI leverage from expensive noise.
Track AI spend, adoption, code impact, and engineering outcomes to separate measurable leverage from trend-driven cost.
Executive metrics preview
An executive control surface for modern engineering.
Featured insight
Your engineering organization is not under-instrumented. It is under-modeled.
Binomial reveals what activity metrics and isolated tooling cannot.
Why Binomial
Beyond dashboards. Beyond developer tooling.
Not just activity tracking
Modeled outcomes
Not just code scanning
System-level intelligence
Not just visibility
Enforceable control
Not just AI adoption
Measurable AI economics
Not just for engineering
For the business
Final call
Make engineering legible.
Binomial gives leadership a system for understanding how software is built, where risk accumulates, how delivery degrades, what AI is costing, and what it will take to improve.