Ship the internal tools your firm always needed and never built.
Hand Foundry a spec; the AI stands up a full-stack app — front end, back end, dedicated database — running in an isolated sandbox in minutes. The custom workflow tools, internal dashboards, and bespoke client portals your firm has been quoting at six-month timelines start shipping in days.
An AI engineer that actually codes
Foundry isn’t autocomplete. It’s an agent that writes the code, runs the build, watches the output, diagnoses the failure, and iterates — operating as a software engineer, not a copilot. Each app gets its own running container, its own isolated network, and its own dedicated Postgres. The agent ships against real infrastructure.
Your team reviews and redirects. The AI handles the work. The internal tooling backlog that’s been blocking deals, slowing client onboarding, and consuming senior time stops being a quarter-long planning exercise.
"Internal portal for matter intake — Clio sync, document upload, status tracking."
Isolated container, dedicated Postgres, preview URL live. Schema drafted.
Form submits, document uploads, status writes to DB. Test run green.
Living preview shipped to your team. Versioned snapshot saved.
How firms win on Foundry
Three places the engineering bottleneck stops costing you deals.
Software is no longer a quarter-long roadmap exercise. When the AI writes, runs, and iterates, the work that used to require a hiring plan ships from a Friday standup.
Say yes the same week
A client asks for a custom intake portal, a one-off integration, a bespoke dashboard. Your firm says yes the same week — because Foundry stands up the working app inside the time competitors are still scheduling the discovery call.
Tools no one else has
Your firm runs internal software no one else in your category does — workflow apps tuned to how you actually operate. The "we built that ourselves" story your competitors can't tell becomes part of every pitch you make.
The premium stays inside
The roadmap that used to require a quarter of planning and a year of staffing collapses to a backlog the AI works through autonomously. The custom-software premium your firm has been paying outside vendors stays inside the firm.
How it works
Real infrastructure. Real engineering loop. Real apps.
Foundry doesn’t mock. Each app runs against a live container with its own database, its own network, its own preview URL. The AI engineers exactly the way your team would — write code, run it, observe output, diagnose failure, iterate.
Code, run, observe, fix
The agent engineers the way your team would. Every file write, every command run, every error streamed live to your team.
Plan
Decompose the spec into concrete steps — files to write, commands to run, behaviors to verify.
Write & run
Generate the code. Execute against the live sandbox. Stream stdout/stderr to your team in real time.
Observe & diagnose
Read the output. Stack trace? Failed test? Unexpected behavior? Identify the root cause.
Iterate
Revise, re-run, re-observe. Continue until the task is complete or the agent escalates a question to your team.
Isolated by design. Versioned by default.
Each app gets its own running infrastructure. No cross-contamination, no production risk, no leaking dependencies.
Running app server scoped to one app. Resource-limited, network-isolated, ephemeral.
A real database the agent writes schemas, runs migrations, and queries against. Destroyed with the sandbox.
The canonical file tree, persistent across sessions. Resume work from any prior point.
Every checkpoint snapshotted. Browse, diff, restore. Engineering work is reversible.
Build the software your firm has always wanted to ship.
Hand the AI a spec. Watch it stand up the app. The internal tooling premium stays inside your firm.