Planhat vs Streak
Side-by-side trajectory, velocity, and editorial themes.
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.
Streak's MCP server now writes — Claude and ChatGPT can create boxes, move deals — plus AI citations.
Streak is at full AI-CRM tilt. The MCP server is no longer read-only: LLMs like Claude and ChatGPT can now create boxes, update fields, move deals between stages, create contacts and organizations, add comments, log Gmail emails, and even create custom-column options. AI outputs now show inline citations and a reference section, so users can verify which email, meeting, note, or web page fed each claim. AI Q&A landed on mobile. Deal summaries and Q&A live in the Gmail sidebar. Around the AI layer, smaller releases combined the stages/columns manager and rebuilt the saved-view editor for keyboard-first speed.
Streak is becoming the Gmail-native CRM that's fully drivable by LLMs — read, write, and audit. The citation system is the trust layer that has to land before MCP writes get used at scale, and the mobile Q&A surface tells you they want Streak AI to be ambient rather than confined to the desktop pipeline view. The non-AI work (phone search normalization, saved view editor, fixes) is the substrate keeping the AI features honest as adoption grows.
Expect MCP writes to extend to pipelines (create a pipeline from a description), task automation (LLMs creating multi-step tasks), and templated workflows. Citations will likely expand to attribute specific column values and fields. Pricing pressure around AI credits is likely as the surface gets wider.
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