AI-powered business operations. GHL. Canopy. Claude.
LaunchWise is a joint venture with EvThatGuy. An AI-powered business platform that integrates GoHighLevel CRM, Canopy tax software, and Claude AI into a unified dashboard for automated business operations. Fourteen modules covering lead scoring, financial modeling, document processing, client onboarding, and more. Built to deployable state in two months with 392+ passing tests.
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Modules built
Strategy, finance, marketing, and ops
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Tests passing
Unit, integration, and E2E suite
2 mo
Ship time
Empty repo to deployable state
SaaS
Category
AI-powered business platform
The Challenge
GoHighLevel, Canopy, and Claude AI are three completely different systems with different APIs, different data models, and different auth patterns. The vision for LaunchWise was to make them behave like a single platform, where a lead entering GHL triggers an AI analysis that pulls financial context from Canopy and outputs a scored recommendation.
The integration complexity was real. GHL webhooks need reliable ingestion. Canopy OAuth tokens expire and need silent refresh. Claude outputs need to be structured and versioned so they can be stored, compared, and audited. A sync failure in any layer should not cascade into broken UI or corrupted records.
With a two-month timeline and a 14-module scope, the architecture had to be modular from day one. Each module needed to be independently testable, which is why 392+ tests exist before the platform even hits production.
Platform Modules
Claude AI analyzes inbound leads from GoHighLevel and assigns a fit score based on configurable business criteria. High-scoring leads trigger automated follow-up sequences in GHL.
AI-assisted scheduling that reads calendar availability, client preferences, and pipeline stage to suggest optimal meeting times. Confirmed appointments sync back to GHL automatically.
Automated ingestion and analysis of business documents, contracts, and financial statements. Claude extracts key data points and surfaces them in structured summaries for decision-making.
Guided onboarding flow that collects business context, integrates with GHL contacts, and generates a personalized AI business plan on completion. First-session value delivery.
Canopy-connected financial analysis that normalizes accounting data for AI input. Claude generates projections, identifies anomalies, and flags areas needing attention.
Multi-step AI workflow that produces a structured business plan from user inputs. Prompt chaining breaks the generation into phases so each section builds on the last with context.
AI-generated channel recommendations and campaign outlines based on business type, target audience, and budget. Outputs can be pushed directly into GHL campaign templates.
Aggregated view of AI activity, GHL pipeline metrics, Canopy financial data, and module usage. Org admins see a single source of truth across all connected systems.
Integration Layer
CRM and automation
Tax and accounting
Business intelligence
Test Coverage
The 392+ tests are not a vanity number. Each integration has its own test boundary. GHL sync tests mock the REST API and verify contact write-back logic independently of Canopy. Canopy tests verify OAuth refresh behavior without touching GHL. Claude output tests validate Pydantic model parsing against fixed prompt responses.
The multi-tenant data layer has its own isolation tests. Org-level row isolation is verified so that one tenant's data cannot leak into another tenant's queries. Every module that writes AI output has tests that verify versioning and retrieval.
System Map
Data Flow
Tech Stack
Deliverable
LaunchWise went from concept to deployable platform in two months. Fourteen modules operational. All three integrations live: GoHighLevel syncing contacts and pipeline data, Canopy providing financial context, and Claude AI generating and versioning structured business outputs.
The 392+ test suite means the platform is not deployable in theory, it is deployable with confidence. Every data boundary is tested. Every integration has a failure mode that degrades gracefully rather than propagating errors across modules.
This was a joint build between MGT and EvThatGuy, two developers working in parallel across frontend and backend, coordinated through a shared API contract from day one. The architecture supported parallel work without merge conflicts or integration surprises.
Whether it is a GHL integration, a Claude-powered workflow, or a multi-tenant SaaS with complex data requirements, book a call and we will scope it out.