Affinity vs Twenty
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.
Twenty's open-source CRM hits v2.5 while wiring AI agents and credit-metered billing into the workflow core.
Twenty is shipping fast on its v2.x line, with five releases across April and May pushing AI agents as first-class workflow nodes and rolling out a billing v2 that meters AI credit usage. The release cadence shows the cost of that ambition: a string of cross-version upgrade hotfixes, agent-node execution bugs, and modal-loading regressions has accompanied the new surface area. The team is leaning into incremental hotfixes (v2.5.0 to v2.5.3 within four days) rather than batching.
AI agents and credit-based metering are becoming structural to the product, not optional add-ons — the architecture is being reshaped to gate billing at AI entry points rather than per workflow step. Meanwhile the workspace migration runner keeps surfacing cascade-dependency bugs as the schema evolves, suggesting an underlying brittleness that will need a structural fix. The pattern is: new capability ships, upgrade paths break, hotfix lands.
Expect a consolidation release that hardens the workspace migration runner against cascading column dependencies — the recurring pattern of fixing this case-by-case (v2.5.0, then the band-aids in #20581/#20583) signals a refactor is overdue. AI agent capabilities will continue expanding as the credit-cap architecture matures.
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