ExperimentOps Development for Experiment Lifecycle Management

Bringing experiment setup, analysis, and product decisions into one workspace.

ExperimentOps is a SaaS platform for product and growth teams to manage the full experiment lifecycle from defining a hypothesis and launching a test to analyzing results and documenting what happens next.

We built the platform with Next.js and FastAPI, connecting experiment configuration, traffic assignment, metric collection, statistical analysis, and decision tracking.

Experimentation workflows can become fragmented across analytics tools, spreadsheets, and documents. Teams may track results in one place while recording the final decision somewhere else, making it difficult to connect what was tested, what was learned, and why a change shipped.

ExperimentOps was built to keep that workflow connected and preserve the reasoning behind each decision.

Experiment setup: Define hypotheses, configure variants, allocate traffic, set audience rules, and select success metrics.

Consistent variant assignment: Assign subjects deterministically so they receive the same variant within an experiment.

Metric ingestion and monitoring: Collect experiment events and monitor running tests.

Statistical and segment analysis: Evaluate results and explore differences across audience segments.

Decision tracking: Record ship, iterate, or stop decisions alongside the analysis and supporting rationale.

Team workspaces: Support multiple organizations, role-based permissions, shared metric definitions, and audit history.

The core challenge was maintaining consistency across the experiment lifecycle. Configuration, assignment, incoming events, analysis, and decisions needed to follow the same rules and remain connected.

The platform also required strict separation between organizations. Tenant-scoped application access and PostgreSQL row-level security protect workspace boundaries, while role-based permissions control what each team member can do.

Statistical interpretation was another important concern. Analysis snapshots provide a stable reference for decisions, preserving the results that informed the team’s conclusion.

A working platform that connects experiment execution with documented product decisions. Teams can follow an experiment from its initial hypothesis through results and retain a searchable history of what they learned.

Built as an independent portfolio product, ExperimentOps demonstrates full-stack SaaS development across multi-tenant architecture, data ingestion, statistical analysis, and collaborative workflows.

Our role: Product Developent, Desgin & Engineering Technology: Next.js · React · TypeScript · Tailwind CSS · Python · FastAPI · PostgreSQL · SQLAlchemy · SciPy