Stride

The third feature group combines the Optimize and Verify modules. Optimize uses process mining to discover bottlenecks in the delivery workflow—recurring handoffs, delays, and automation opportunities—and quantifies their impact on cycle time. It can identify millions in automation savings, as shown by a global logistics company that found $2.1M in previously unknown efficiencies. Verify handles all testing aspects: it generates test cases (including Gherkin) from stories, predicts defect risk for each change, and enforces quality gates before release. The module proposes regression tests grounded in past defects, and its risk-based prioritization can reduce regression suite size by 60% while catching three times more bugs pre-release. Both modules share the same connected graph, so a defect raised in Verify automatically links back to the story and diagram that produced it.

Stride works by representing every delivery artifact as a node in a single connected graph. When a story moves to “In Progress,” its linked tests light up; when architecture drifts, the stories that depend on it surface. This live traceability matrix replaces the “whose job is this?” meetings common with fragmented tools. The platform acts as an MCP server, allowing AI coding agents like Claude Code and OpenAI Codex to read and update the workspace directly from the CLI or IDE, with full RBAC, audit logging, and budget caps. Setup is under two minutes: import from Jira or CSV, describe the project’s tech stack and goals, and the AI immediately generates context—stories, architecture options, test strategies—without months of configuration. Every AI call is grounded in the workspace graph, not a separate prompt.

Concrete use cases from real teams demonstrate Stride’s impact. A Fortune 500 SaaS company’s VP of Engineering reported sprint planning dropped from half a day to 30 minutes, with 92% of AI-generated stories accepted without edits. A global logistics head of operations found $2.1M in automation savings through the Optimize module, making executive buy-in straightforward. A top-10 US bank’s QA director cut regression testing time by 60% and caught three times more defects before release using Verify’s risk-based prioritization. A principal solution architect at an enterprise cloud platform generated three scored architecture options in minutes, replacing weeks of whiteboarding sessions. An engineering manager at a Series C AI startup consolidated five tools into one, increasing delivery velocity by 34%. These outcomes span fintech, SaaS, logistics, banking, and infrastructure.

Stride targets product and engineering teams of all sizes, from three-person startups to 150-person enterprises. Pricing is per-seat monthly: Starter at $9/seat (Plan + Verify, 3 projects, 150 AI credits/seat), Pro at $29/seat (all four modules, unlimited projects, 800 credits/seat, audit log, webhooks), and custom Enterprise with SSO, data residency, and on-prem options. Integrations are live with GitHub, Slack, Jira Cloud, Claude Code, OpenAI Codex, and a REST API plus webhooks for everything else. Security includes AES-256 encryption, TLS 1.2+, bcrypt password hashing, and RBAC on every mutation. Stride’s core promise is eliminating tool sprawl by providing a single AI-native platform where every artifact is connected, enabling teams to plan, design, build, and ship as one system with dramatically higher velocity and confidence.

Updated 2026-06-17