Michael Chihlas 8e9d22e0e0 feat(escalations): magic-moment handoff-context screen on pickup
Adds the dedicated 4-section handoff-context view that renders BEFORE
the FlowPilot session for senior techs picking up an escalated
session, then dissolves on "Start here". This is the wedge's
demonstrable magic moment — what the GTM Loom records.

- HandoffContextScreen.tsx: pure presentational, takes a HandoffResponse
  plus onStartHere / onDismiss callbacks. Sections: header
  (problem summary, domain, step count, escalated-time, priority badge),
  "What's been tried" (engineer notes + step-count affordance), "AI
  assessment" (likely_cause / suggested_steps / confidence badge), Start
  here CTA. Confidence badge accepts both numeric (0..1) and string
  ("low"/"medium"/"high") shapes — backend currently emits the latter.
  Renders an explicit "assessment unavailable" branch when
  ai_assessment_data is null (the 5s timeout from 9bdd995 fired).
  Honors prefers-reduced-motion (animate-fade-in vs animate-slide-up).
  ARIA dialog + focus on the primary CTA. Esc dismisses when used as a
  re-openable overlay; pre-claim, Start here is the only exit.

- FlowPilotSessionPage.tsx: on /pilot/:id?pickup=true, fetch the
  handoff list via handoffsApi.listHandoffs (account-scoped via RLS,
  no claim required) and find the latest unclaimed escalate handoff.
  If found, render the magic-moment screen and skip the regular
  loadSession (the senior isn't yet escalated_to_id, so GET would
  404). Start here calls claimHandoff, drops the pickup query param,
  dismisses the screen — the existing loadSession effect then fires
  because the senior is now escalated_to_id. A "Context" toolbar
  button on active sessions re-opens the screen as a dismissible
  overlay (visible only when the senior arrived via the magic-moment
  flow this session — handoff lookup on demand).

Verified end-to-end against the running dev stack: listHandoffs
returns the unclaimed handoff with full payload; claim flips session
status from escalated → active; subsequent GET succeeds. tsc -b clean.

Defers (TODO followups): suggested-step chips below the chat input
that prefill on click (requires threading through to
FlowPilotMessageBar); snapshot expansion to include the recent
diagnostic steps pre-claim; toolbar Context button on sessions where
the senior didn't arrive via magic-moment.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-27 21:06:14 -04:00
2026-04-24 23:17:06 -04:00
2026-04-24 23:17:06 -04:00

ResolutionFlow

Stop writing ticket notes. Start generating them.

ResolutionFlow is an AI-powered troubleshooting platform for MSP professionals. Engineers follow guided flows while an AI copilot assists — and documentation writes itself as a byproduct of the work.

Production: resolutionflow.com


Quick Start

# Prerequisites: Docker, Python 3.11+, Node.js 20+

# Start PostgreSQL
docker start patherly_postgres

# Backend
cd backend
source venv/bin/activate
pip install -r requirements.txt
alembic upgrade head
uvicorn app.main:app --reload

# Frontend (separate terminal)
cd frontend
npm install
npm run dev

See DEV-ENV.md for full environment setup (devserver, Docker, CORS).


Features

FlowPilot AI Copilot

Like having a senior engineer on every call. FlowPilot guides troubleshooting decisions, suggests next steps with context-aware intelligence, and automatically captures documentation as a byproduct of the session.

  • Confidence-tiered model routing (fast responses for simple steps, deeper reasoning for complex decisions)
  • AI-generated ticket summaries and session documentation
  • Standalone assistant chat with RAG for open-ended troubleshooting
  • Knowledge Flywheel: AI analyzes completed sessions and proposes new flows automatically

Guided Flows

  • Troubleshooting Flows — Decision trees with branching paths for diagnosing issues
  • Procedural Flows (Projects) — Step-by-step checklists for onboarding, migrations, deployments
  • Maintenance Flows — Scheduled recurring tasks with batch execution across multiple targets
  • Visual Flow Editor with drag-and-drop canvas, undo/redo, markdown support
  • AI Flow Builder — describe what you need, get a complete flow generated

Auto-Documentation

Every session generates timestamped, detailed notes formatted for your PSA. Engineers never write another ticket note.

  • Export to Markdown, plain text, or HTML
  • Sensitive data redaction
  • One-click push to ConnectWise PSA tickets

ConnectWise PSA Integration

  • Post session documentation directly to ConnectWise tickets as internal notes
  • Pull ticket details and client context into FlowPilot sessions
  • Member mapping between ResolutionFlow and ConnectWise users
  • Credentials encrypted at rest (Fernet), stored per-team

Team & Knowledge Management

  • Role-based access (super_admin, team_admin, engineer, viewer)
  • Shared flow library with categories, tags, folders, full-text search
  • Step Library — reusable troubleshooting steps with ratings and reviews
  • Session sharing via link (authenticated and public views)
  • Escalation workflow with AI-enhanced briefing packages
  • Flow proposals from AI analysis (review queue for team leads)

Tech Stack

Layer Technology
Frontend React 19, TypeScript, Vite, Tailwind CSS v4
State Zustand (immer + zundo for undo/redo)
Routing React Router v7
Canvas @xyflow/react (React Flow) + dagre
Backend Python FastAPI, async SQLAlchemy 2.0 + asyncpg
Database PostgreSQL 16
Migrations Alembic (75+ migrations)
Auth JWT (python-jose) + bcrypt, refresh token rotation
AI Anthropic Claude API (tiered model routing)
Embeddings Voyage AI (semantic search)
Scheduling APScheduler 3.x (async)
Analytics PostHog
Hosting Railway (auto-deploy on push to main)

Project Structure

patherly/
├── backend/
│   ├── app/
│   │   ├── main.py                 # FastAPI entry point
│   │   ├── api/endpoints/          # Route handlers (35+ endpoints)
│   │   ├── core/                   # Config, database, permissions, security
│   │   ├── models/                 # SQLAlchemy models
│   │   ├── schemas/                # Pydantic schemas
│   │   └── services/psa/           # PSA provider abstraction layer
│   ├── alembic/                    # Database migrations
│   └── tests/                      # Integration tests (100+)
├── frontend/
│   ├── src/
│   │   ├── components/             # UI components by domain
│   │   ├── pages/                  # Page components
│   │   ├── store/                  # Zustand stores
│   │   └── types/                  # TypeScript interfaces
├── docs/                           # Design docs, plans, ConnectWise reference
├── brand-assets/                   # SVGs, brand guide
├── CLAUDE.md                       # AI assistant project context
├── CURRENT-STATE.md                # Detailed feature status
└── CHANGELOG.md                    # Release history

Running Tests

# Backend integration tests
cd backend
pytest --override-ini="addopts="

# Frontend build (stricter than tsc --noEmit)
cd frontend
npm run build

Documentation

Document Purpose
CLAUDE.md Full project context for AI-assisted development
CURRENT-STATE.md Detailed feature status
03-DEVELOPMENT-ROADMAP.md Development roadmap
UI-DESIGN-SYSTEM.md Design system (Slate & Ice)
DEV-ENV.md Development environment setup
CHANGELOG.md Release history

License

Proprietary. All rights reserved.

Description
Troubleshooting decision tree application for MSP engineers - automatically generates professional documentation from guided diagnostic workflows
Readme 16 MiB
Languages
Python 54.7%
TypeScript 43.5%
HTML 1.1%
CSS 0.6%