Michael Chihlas 9f0bfd44f9 feat(escalations): mount time-to-first-action stat-card on /escalations
Surfaces the new GET /analytics/flowpilot/escalations endpoint as a card
above the EscalationQueue list. Closes the loop from yesterday's metric
endpoint commit — seniors and owners see the wedge stat the moment they
open the queue, which is the daily-reps version of the GTM ROI story.

Pieces:
- EscalationMetrics TS interface mirroring the backend Pydantic model
  (incl. metric_definition disclaimer field)
- flowpilotAnalyticsApi.getEscalationMetrics(period) client method
- EscalationMetricCard component:
    * loading skeleton, error state, zero-data empty state
    * avg + median + n_with_action/n_claimed conversion rate
    * humanized seconds → "Ns" / "N.N min" formatting
    * inline disclaimer reminding callers this is in-product time-to-
      first-action only, NOT the savings claim — pair with manual
      baseline (per /codex review's two-metric correction)
- Wired into EscalationQueuePage above EscalationQueue

DS-aligned: card-flat, accent-dim usage held to interactive elements,
text-muted-foreground for secondary copy, font-heading on the headline
number, explicit transition properties (no `transition: all`). Respects
prefers-reduced-motion implicitly (only animation is the loading pulse,
which Tailwind's animate-pulse already gates).

tsc -b clean. No new tests in this commit — component is a thin
state-machine over an axios call; integration coverage comes from the
existing backend tests + the e2e Playwright work in the plan.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-27 16:00:34 -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%