e8ba74ed6dabc77f329341f9576cacce0f044ab9
Three improvements driven by live wedge testing.
1) Notification title now includes a problem snippet and PSA ticket
suffix when present:
"Escalation from Jane · #12345: Outlook is failing to sync email…"
Replaces the prior "Session escalated by Jane" copy that made every
escalation from the same junior look identical in the bell panel.
Snippet is trimmed to 70 chars with ellipsis. handoff_manager now
passes psa_ticket_id through in the notify() payload so this works
for both /escalate and /handoff entry points.
2) AI enrichment (assessment + enhanced escalation_package) moved to
a FastAPI BackgroundTask. The escalating engineer no longer waits
on 15-25s of Sonnet latency — handoff creation returns as soon as
snapshot, status flip, dual-write, documentation, PSA push, and
notify() are committed. enrich_escalation_async opens its own DB
session, runs both AI calls, updates handoff.ai_assessment +
session.escalation_package, commits, and publishes a new
`handoff_assessment_ready` event on the escalation bus. Frontend
doesn't yet listen for that event — the magic-moment screen still
shows a placeholder ("AI assessment is still generating. Reopen
this view in a few seconds…") which is honest about the state.
Live polling / auto-refresh on the bus event is the natural next
step.
3) ChatSidebar entries now surface the problem summary as a secondary
line and tag PSA-linked sessions with a monospace #ticket badge plus
an "Escalated" pill on in-transit sessions. ChatListItem grew
problem_summary, psa_ticket_id, and status fields; loadChats
populates them from listSessions. The user couldn't tell their own
sessions apart in the sidebar because they all rendered as "New
Chat" with no distinguishing detail — this fixes that for any
session, escalated or not.
Test plan
- Backend full suite: 1103 passed in 255.85s with -n auto.
- Frontend tsc -b clean.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
fix: replace all remaining old brand tokens (text-brand-dark, border-brand-border, bg-white opacity)
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
- Frontend: http://localhost:5173
- Backend API: http://localhost:8000
- API Docs: http://localhost:8000/api/docs
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
Languages
Python
54.7%
TypeScript
43.5%
HTML
1.1%
CSS
0.6%