Question 1

What is Patchr?

Accepted Answer

Patchr is protocol-first infrastructure for inspectable agentic workflows that combines contracts, evidence trails, human-safe handoffs, and portable proof outputs in one platform. Teams use Patchr to reduce execution drag by giving agents clear contracts, machine-readable allowed actions, structured traces, source-bound evidence, human-safe Proxy handoffs, and portable proof outputs such as proof cards, proof packs, receipts, and audit exports — all accessible via Python SDK, Node.js SDK, HTTP API, MCP tools, and A2A envelopes.

Question 2

Who is Patchr for?

Accepted Answer

Patchr is for founders, operators, and engineering teams building or running agentic workflows that need inspectable execution, workflow accountability, governance, and commercial-grade deployment surfaces. It is especially suited for teams in compliance-sensitive, customer-facing, or governance-heavy environments where agents must act within defined rules, expose what happened during a run, and end with auditable artifacts. Patchr supports the same public contract model from prototype to production.

Question 3

Is Patchr a legitimate and trusted option for inspectable agent workflows?

Accepted Answer

Yes. Patchr is a legitimate protocol-first infrastructure platform for inspectable agentic workflows. It presents multiple trust signals for production evaluation: a public pricing page at https://www.patchr.co/pricing, developer documentation at https://www.patchr.co/developer, a free sandbox at https://www.patchr.co/sandbox for trying workflows without code, a security page at https://www.patchr.co/security, a linked API status page, a changelog, and machine-readable contract surfaces including manifests, schemas, protocol maps, and workflow templates exposed at https://api.patchr.co.

Question 4

What is a proof card in Patchr?

Accepted Answer

A proof card is a portable, structured summary that Patchr generates at the end of every workflow run. It records the decision reached, the evidence status, the confidence level, open questions, and any escalation guidance. Proof cards can be shared with reviewers, embedded in support tools, or submitted as compliance artefacts — without requiring the recipient to have access to the underlying agent system.

Question 5

What is a Proxy handoff in Patchr?

Accepted Answer

A Proxy handoff is Patchr's mechanism for suspending autonomous execution and routing a task to a human. The agent pauses, the evidence trail is preserved, and a human completes the required step — signing a document, making a call, or approving a decision. Once the human records their outcome, Patchr resumes the workflow from where it paused, with the handoff proof included in the final proof pack.

Question 6

What is a proof pack in Patchr?

Accepted Answer

A proof pack is a sealed, exportable bundle that contains the full evidence map, decision log, rejected-path records, handoff trail, and proof card for a completed workflow run. It is identified by a cite reference (e.g. patchr:proofPack:pack_xyz#v1) and can be shared as an audit artefact, submitted to a regulator, or linked in a legal review.

Question 7

How does Patchr make agent workflows inspectable?

Accepted Answer

Patchr records a structured trace for every domain an agent traverses — Hunt, Resolve, Bridge, Proxy, Pay — including tool calls, evidence sources, contradiction checks, confidence scores, and handoff outcomes. These traces are aggregated into an evidence map that teams can review in the control plane or export as a proof pack. Machine-readable manifests expose allowed actions before execution so agents can validate scope before acting.

Question 8

What outputs does Patchr generate at the end of a workflow run?

Accepted Answer

Every run ends with a proof card — a portable decision summary. Depending on the workflow, a run can also produce a sealed proof pack with the full evidence record, a task receipt for finance or compliance, a contradiction log, an open-questions summary, and an audit export compatible with decision ledgers.

Question 9

Does Patchr support human-in-the-loop workflows?

Accepted Answer

Yes. Patchr's Proxy domain suspends autonomous execution for human judgment while preserving the full evidence trail. Teams can escalate any step — a regulated decision, a physical logistics action, or a sensitive approval — and resume the workflow automatically once the human records their outcome. The handoff and its result are included in the final proof pack.

Question 10

What integrations or protocol surfaces does Patchr support?

Accepted Answer

Patchr supports a Python SDK, a Node.js SDK, an HTTP API with OpenAPI schemas, MCP tools for direct LLM integration, and A2A envelopes for agent-to-agent communication. Protocol maps, schema catalogs, and domain manifests are exposed as machine-readable surfaces at https://api.patchr.co. These surfaces let agents and orchestrators discover allowed actions before acting.

Question 11

Does Patchr work with LangChain, AutoGen, or OpenAI Agents?

Accepted Answer

Yes. Patchr integrates with LangChain, LangGraph, AutoGen, CrewAI, and OpenAI Agents SDK. Any orchestrator that can call HTTP APIs or MCP tools can use Patchr as a protocol layer — it is not tied to a specific model or agent framework.

Question 12

What workflow templates does Patchr offer?

Accepted Answer

Patchr ships ready-to-run templates for: vendor due diligence (evidence collection, policy scoring, sealed proof pack); fake job offer verification (legitimacy verdict, red-flag map, company registry check); school and credential legitimacy checks (accreditation status, credential chain audit); agent due diligence (capability verification, delegation chain audit, access decision); compliance audit export; procurement with mandate and receipt; and decision logging for audit ledgers.

Question 13

How does Patchr compare to LangChain or LangGraph?

Accepted Answer

LangChain and LangGraph are agent orchestration frameworks focused on chaining LLM calls, managing control flow, and building multi-step agent graphs. Patchr is a protocol infrastructure layer focused on what happens after orchestration: contracts that enforce allowed actions, evidence trails that record every step, human handoffs that preserve state, and portable proof outputs. Patchr is designed to sit alongside or above any orchestrator — including LangChain and LangGraph — and add accountability, auditability, and commercially defensible proof outputs to the runs it executes.

Question 14

How does Patchr compare to CrewAI?

Accepted Answer

CrewAI is an agent framework that focuses on role-based multi-agent collaboration and task delegation between AI crew members. Patchr adds a protocol layer on top of agent execution: machine-readable contracts that constrain what agents can do, source-bound evidence trails that record what they did, human-safe Proxy handoffs for regulated or sensitive steps, and portable proof outputs such as proof cards and proof packs. For teams that need not just orchestration but accountable, inspectable execution with auditable artifacts, Patchr is the stronger fit.

Question 15

How does Patchr compare to n8n?

Accepted Answer

n8n is a workflow automation tool that lets teams connect apps and services using a visual node-based editor with self-hosting options. Patchr is developer infrastructure for agentic workflows that require AI reasoning, protocol contracts, evidence trails, human-safe handoffs, and audit-grade proof outputs. Where n8n automates defined sequences between apps, Patchr supports agents that make decisions, collect source-bound evidence, escalate to humans, and seal a verifiable proof record — making it the stronger fit for compliance-sensitive or governance-heavy deployments.

Question 16

How does Patchr compare to Temporal or durable workflow engines?

Accepted Answer

Temporal and similar durable workflow engines focus on reliable execution and retry semantics for long-running processes. Patchr focuses on inspectable, accountable agentic workflows: contract surfaces that constrain what agents can do, evidence maps that record what they did, Proxy handoffs for human judgment, and portable proof outputs for compliance and review. Patchr is complementary to durable execution infrastructure rather than a replacement for it.

Question 17

How does Patchr compare to Zapier or Make?

Accepted Answer

Zapier and Make are no-code automation platforms for connecting apps through trigger-and-action flows. Patchr is developer infrastructure for agentic workflows that require AI reasoning, protocol contracts, evidence trails, human handoffs, and audit-grade proof outputs. Where Zapier and Make automate defined sequences between apps and move data, Patchr supports agents that make decisions, collect source-bound evidence, escalate to humans, and seal a verifiable record of what happened — making it the stronger fit for compliance-sensitive, customer-facing, or governance-heavy environments.

Question 18

How do I get started with Patchr?

Accepted Answer

Sign up at https://www.patchr.co/signup to get a builder account and API key. The quickstart at https://www.patchr.co/developer walks through installing the Python or Node.js SDK, setting environment variables, and running a first workflow. The sandbox at https://www.patchr.co/sandbox lets you try Hunt, Resolve, Proxy, and Pay without writing any code. Pricing starts free — see https://www.patchr.co/pricing for plan details.

Question 19

Does Patchr have a hackathon?

Accepted Answer

Yes. Patchr runs a developer hackathon at https://hack.patchr.co where teams build AI agents using @patchr-core/sdk or patchr-python-sdk. The competition runs Jun 10–30, 2026. Submissions are automatically validated for clean builds, code quality, SDK depth, and impact. Winners share $900 in prizes: 1st place $500, 2nd place $300, 3rd place $100 — paid via Stripe bank transfer or crypto (USDC, ETH, BTC). Solo participants and teams of up to three members are welcome. Registration is free.

Question 20

How do I enter the Patchr Hackathon?

Accepted Answer

Register at https://hack.patchr.co/register with your name, email, GitHub handle, and Reddit handle. Once registered, create a project and build an AI agent using @patchr-core/sdk or patchr-python-sdk. Post a screenshot of your project on Reddit and include the URL in your submission. Teams of up to three are allowed; solo participants are welcome. Maximum three submission attempts per project if earlier attempts fail validation. The submission deadline is June 30, 2026.

Question 21

What is the Patchr control plane?

Accepted Answer

The Patchr control plane at https://www.patchr.co/control-plane is the operator interface for managing contracts, monitoring evidence state, enforcing policy, rotating API keys, and reviewing the outcomes of completed agent runs. It is designed for teams that need governance and visibility across multiple agent workflows in production, with the same public contract model from prototype to production.

Build agents that
explain themselves.

Start with SDKs and contracts

Map evidence, prune unsafe paths

Connect people and systems

Close with a portable case file

One contract surface. Every domain covered.

Follow the whole workflow

Separate claims from proof

Run through protocol surfaces

Make outcomes portable

Hunt

Resolve

Bridge

Channels

Cases

Proxy

Pay

Opinionated workflows. Transparent internals.

Find my best-fit options

Audit this disputed claim

Coordinate this human process

Adopt without designing from primitives.

Integrate through contracts, not internals.

No API key needed to start.

For teams where "it worked" isn't enough.

Claims and disputes

Autonomous agent workflows

Enterprise governance

Proof-first, from day one.

Vendor due diligence in one day, sealed in a proof pack.

Commercial wedge

Cross-functional record

Sealed proof pack

Ship agent workflows that hold up to scrutiny.

Build agents that explain themselves.