PatchBuddy isn't one trick. It's a full delivery surface: chat-driven build, live diagram, knowledge accumulation, multi-tenant access, model choice across every frontier provider, cost transparency, test runs, audit. All behaving like one product.
When a Patchworks flow goes sideways at 2am you need to know fast and need to understand fast. Two new surfaces in the dashboard do exactly that. Drill into any order from a dedicated lookups view. Get pinged the second something fires, with the diagnosis already written. PII redacted by default on both.
A dedicated lookups view in the PatchBuddy dashboard. Paste an order ID; the agent deep-dives its tracked data inside Patchworks and returns a complete report. Every payload, every transformation, every step it touched. Skip the canvas archaeology.
A deployable script that hooks into any Patchworks flow. When something fires, the Slack notification carries an AI-generated diagnosis with it: what failed, why, the upstream context. Useful when you've burned through Patchworks' own email limits and need a channel that scales.
Tell PatchBuddy what you need in plain English. It picks the right shapes, configures connectors with your existing credentials, writes the mappings, adds caches, branches, dedup, error handling. You watch it happen on the live diagram. Every change is instantly verifiable in Patchworks.
The flow drawer renders alongside the chat. Every shape, every edge, every config decision shows up as PatchBuddy works. Click "View in Patchworks" to jump straight into the canvas. Same flow, fully editable.
PatchBuddy trains its selected frontier models by proxy: every successful build, every error caught, every pattern your agency standardises gets distilled and routed back into model context, so the next turn benefits, the next project benefits, and the agency's house style accumulates without anyone managing it.
The models stay full-fidelity. We don't quantise, distil, or self-host. The frontier checkpoints PatchBuddy routes to are the same ones you'd hit calling Anthropic, OpenAI, or DeepSeek directly. The learning happens around them, not inside them.
Every gotcha, every decision, every pattern your team uncovers gets stored in project knowledge. The next task automatically pulls in the relevant context. New developers ramp on day three; veterans stop solving the same problem twice.
More than that: PatchBuddy's platform-level knowledge is open. You can read every pattern the agent has learned, every gotcha it's catalogued, every default it ships with. Disagree with how something's documented, or want to handle a Patchworks pattern differently for your agency or one specific client? Fork it. Your forked version overrides the platform default for everyone in your scope; the original keeps serving everyone else.
Every end-customer is an isolated organisation with its own credentials, projects, knowledge, and chat history. Pivot-based access at the agency level. Your team's reach is managed once, not per-client.
Run a flow with a real payload from the source system. PatchBuddy captures the response and uses the actual schema for downstream mapping. No more "looks fine to me" deploys that break in production on the first real record.
Token spend visible at chat, message, and turn level. Cache hit ratios, model selection, time-per-iteration. All on tap.
Chat sent, project created, task completed, credentials updated. All logged with actor, agency, scope, and time.
When PatchBuddy needs sign-off, buttons render inline. Friction-free plan-approve cycles.
When PatchBuddy needs three or more details, it renders a form pre-populated with your existing connectors and entity types.
Screenshots, sample JSON, HAR captures. All read by the agent and incorporated into the next response.
Spin up a 1:1 copy of any task or knowledge entry into your agency's own workspace. Try-this-approach experiments without disrupting the original.
Sign up, drop in your Patchworks credentials, watch a real integration build by chat. Start to ship in one session.