Bridge gives you everything you need to harness AI's full potential: from discovery, documentation, and refinement to easily delivering multiple tickets in parallel.
Give your SFCC team superpowers
The Accelerator wraps guardrails around AI so you get the speed without the technical debt. Click below to see how it works.
Turn a scoped ticket into a reviewed pull request against your real cartridge, or hand the plan to Copilot, Cursor, or Claude Code and let them fly with guardrails on.
Estimates and plans grounded in your actual code, plus ticket reviews that catch gaps before a developer ever picks up the work.
Multi-model code review and Commerce Cloud log monitoring put strong guardrails around you, and when something breaks, Bridge tells you how to fix it.
Bring a real challenge from your roadmap and we'll walk through exactly how the Accelerator would handle it, on your stack.
What it actually is
Many teams are struggling to get value from AI, and are cobbling together fragile and incomplete solutions. We give you everything you'll need from end to end.
For the enterprise architect or VP of Engineering who loses sleep over technical debt and security.
Not an unguided missile
Every line generated is audited against your project-aware engineering playbook before a human sees it. It reads your existing patterns so new code never introduces architectural regressions.
Not a hallucination lottery
Using a localized MCP server, it compiles, lints, and runs tests in an isolated environment first, catching breaks autonomously so they never hit your PR queue.
Not an undocumented mess
Bridge delivers the code and the explanation, deep inline documentation and a clean compliance summary for every major change, perfectly packaged.
For the engineering manager clearing the backlog, boosting sprint speed, and reclaiming senior engineering hours.
Not a code firehose
Instead of flooding the PR pipeline with unverified boilerplate, it filters out early bugs autonomously, turning tedious reviews into quick final approvals.
Not a context switcher
It picks up the task from your tracker, maps the implementation strategy, and writes the code straight into your branch, no tool-hopping.
Not stuck on Friday afternoon
By cutting the 2-to-3 day lag waiting on manual reviews, your team clears backlogs faster and ships on a regular, predictable cadence.
For boutique agencies and retail engineering teams building on B2C Commerce and Storefront Next.
Not a generic LLM
Grounded in your specific ecosystem, it understands PWA Kit, LWC vs. React, and custom B2C Commerce cartridges out of the box.
Not a single viewpoint
Every decision is cross-examined by a multi-agent pipeline and checked against a second-opinion system before submission, no lone-model blind spots.
Not blinded by messy data
Bridge reads your schemas, routing rules, and product metadata so everything functions flawlessly in staging, not just on a clean demo.
Bridge is the MCP data layer beneath your AI. It injects your ticket, your repo standards, and your front-end rules straight into the agent, so Copilot, Cursor, and Claude Code stop vibe-coding and start shipping code that fits your architecture.
Is your codebase huge? No problem. Bridge learns from your team's past pull requests and estimates to understand how your project actually works, so you get output tailored to your cartridge, not generic suggestions. Moving to Storefront Next? It builds against React and PWA Kit too.
Want the practical, tool-by-tool breakdown of every stage?
See how it works on Premium Tools
Enterprise control
Bring your own AI, manage your own tokens, and keep automation gated behind human approval.
Bring Claude, GPT, Gemini, or an open model, and let multi-model review cross-check the work. No vendor lock-in.
On an Enterprise plan, route model traffic through your own AWS Bedrock, Google Vertex, or Azure OpenAI account, with usage visibility and no per-seat charges.
Automation pauses at the checkpoints you define, nothing merges or deploys until a human signs off.
Try Bridge on your own codebase, free for 21 days. Go from a rough idea to a reviewed pull request with an easy installation.
