Affinity vs Planhat
Side-by-side trajectory, velocity, and editorial themes.
Affinity is layering AI capabilities onto its PE/VC relationship-intelligence core, but release notes are thin.
Affinity continues positioning as the relationship-intelligence CRM for private capital. The recent feed is mostly marketing and category content — blog posts on network mapping, customer stories, and 2026 predictions — interleaved with a few product-shaped items: an MCP server in beta exposing deal data to AI tools, a Lists rebuild focused on performance and filtering, and references to four new AI features for deal decisions. Structured changelog content is sparse.
The discernible pattern is AI plugged into a vertical CRM rather than reshaping it. MCP server, deal-flow AI, automatic email and meeting capture, and smarter search all layer onto the existing relationship graph. Affinity is doubling down on PE/VC vertical positioning over horizontal CRM competition, and the AI direction looks additive — not a directional rewrite of the product.
Expect the MCP server to graduate from beta and more AI features focused on deal sourcing and portfolio support. Cleaner, dedicated release-note infrastructure would improve external readability, but the strategic direction reads as steady AI layering on a stable PE/VC platform.
Planhat doubles down on automation — Portals, Task dependencies, AI steps, OAuth — for scaled CS ops.
Planhat's recent stream skews heavily toward automation infrastructure for customer-success teams. New advanced Task dependencies, automated end-to-end Portal setup, full execution logs for Automation Runs, and live company-field merge tags in Dashboards and Presentations all reduce the manual per-account work that defines mid-tier CSM tooling. OAuth connections enter Labs, replacing API-key plumbing for integrations.
The product is moving from a health-score-and-playbook CS platform toward a low-code automation backbone for customer-success orgs. Recent additions of frontier LLMs (Claude Sonnet/Opus 4.6, GPT 5.4) into AI Automation steps, combined with portal-creation building blocks, position Planhat as a CS workflow engine that runs without per-account human babysitting.
Expect more native AI step types (action-taking, deeper retrieval), OAuth graduating out of Labs into the standard integrations surface, and continued investment in automation observability — failure analytics, retry policies, version history.
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