You now have all you need to go beyond local pilots and start to see real value from AI
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Our goal with AI is to build the system, not just the agent.
As we've seen customers start to adopt AI workflows on our platform over the last year, we've learned about the complexity of AI in the enterprise. It's not as simple as a personal ChatGPT exploration; getting to outcomes requires an AI platform that is grounded in you.
This September AIP release cuts the cost and friction of putting AI into real workflows—so you can move from a few demos to dozens of dependable automations.
“At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the ingredients for intelligent automation—complete context, comprehensive actions, model interoperability—were ready when the models matured.”
Our goal with AI is to build the system, not just the agent.
As we've seen customers start to adopt AI workflows on our platform over the last year, we've learned about the complexity of AI in the enterprise. It's not as simple as a personal ChatGPT exploration; getting to outcomes requires an AI platform that is grounded in you.
This September AIP release cuts the cost and friction of putting AI into real workflows—so you can move from a few demos to dozens of dependable automations.
“At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the ingredients for intelligent automation—complete context, comprehensive actions, model interoperability—were ready when the models matured.”
Our goal with AI is to build the system, not just the agent.
As we've seen customers start to adopt AI workflows on our platform over the last year, we've learned about the complexity of AI in the enterprise. It's not as simple as a personal ChatGPT exploration; getting to outcomes requires an AI platform that is grounded in you.
This September AIP release cuts the cost and friction of putting AI into real workflows—so you can move from a few demos to dozens of dependable automations.
“At Planhat, we’ve spent a decade making commercial teams more effective and efficient, and built the platform so the ingredients for intelligent automation—complete context, comprehensive actions, model interoperability—were ready when the models matured.”
September AIP release - what is new?
Platform & Models
Model Hub + BYOM: out-of-the-box access to Anthropic, OpenAI, Google, or connect your enterprise model.
Big bump in AI credits across plans to make experimentation practical.
Automations
Native AI Step in Automations: drop AI into any flow without glue code, powering anything from risk identification in conversations to suggesting best next steps ahead of renewals
Tens of AI templates you can turn on in minutes (enrichment, summaries, triage, forecasting helpers, more).
Improved Builder: clearer flow, Branching and Waiting for multi‑step logic.
Signals & Insight
Conversational Intelligence: auto‑categorize + sentiment‑classify emails, tickets, calls; roll up to account, trend over time
AI-powered Health: use conversational intelligence, or any other risk/opportunity agent built in Automations, to drive a more accurate portfolio health forecasting - and implement notifications to act fast
Agents & Context
MCP Server: build agentic workflows that operate across Planhat data + actions.
Documents & Libraries in Automations: Automations can read and generate org docs—tone, strategy, SOPs—so outputs match your practice.
Deployment Support
ADP (AI Deployment Program): specialist team + playbooks to go from first wins to scaled adoption.
___
Our colleague Marco showcased how he uses Planhat MCP + Claude to transform his workflows, directly integrated with Planhat (hint: this Agent Chat interface is coming later 2025).
September AIP release - what is new?
Platform & Models
Model Hub + BYOM: out-of-the-box access to Anthropic, OpenAI, Google, or connect your enterprise model.
Big bump in AI credits across plans to make experimentation practical.
Automations
Native AI Step in Automations: drop AI into any flow without glue code, powering anything from risk identification in conversations to suggesting best next steps ahead of renewals
Tens of AI templates you can turn on in minutes (enrichment, summaries, triage, forecasting helpers, more).
Improved Builder: clearer flow, Branching and Waiting for multi‑step logic.
Signals & Insight
Conversational Intelligence: auto‑categorize + sentiment‑classify emails, tickets, calls; roll up to account, trend over time
AI-powered Health: use conversational intelligence, or any other risk/opportunity agent built in Automations, to drive a more accurate portfolio health forecasting - and implement notifications to act fast
Agents & Context
MCP Server: build agentic workflows that operate across Planhat data + actions.
Documents & Libraries in Automations: Automations can read and generate org docs—tone, strategy, SOPs—so outputs match your practice.
Deployment Support
ADP (AI Deployment Program): specialist team + playbooks to go from first wins to scaled adoption.
___
Our colleague Marco showcased how he uses Planhat MCP + Claude to transform his workflows, directly integrated with Planhat (hint: this Agent Chat interface is coming later 2025).
September AIP release - what is new?
Platform & Models
Model Hub + BYOM: out-of-the-box access to Anthropic, OpenAI, Google, or connect your enterprise model.
Big bump in AI credits across plans to make experimentation practical.
Automations
Native AI Step in Automations: drop AI into any flow without glue code, powering anything from risk identification in conversations to suggesting best next steps ahead of renewals
Tens of AI templates you can turn on in minutes (enrichment, summaries, triage, forecasting helpers, more).
Improved Builder: clearer flow, Branching and Waiting for multi‑step logic.
Signals & Insight
Conversational Intelligence: auto‑categorize + sentiment‑classify emails, tickets, calls; roll up to account, trend over time
AI-powered Health: use conversational intelligence, or any other risk/opportunity agent built in Automations, to drive a more accurate portfolio health forecasting - and implement notifications to act fast
Agents & Context
MCP Server: build agentic workflows that operate across Planhat data + actions.
Documents & Libraries in Automations: Automations can read and generate org docs—tone, strategy, SOPs—so outputs match your practice.
Deployment Support
ADP (AI Deployment Program): specialist team + playbooks to go from first wins to scaled adoption.
___
Our colleague Marco showcased how he uses Planhat MCP + Claude to transform his workflows, directly integrated with Planhat (hint: this Agent Chat interface is coming later 2025).
What you can do now
Fast portfolio visibility
AI‑driven health score: combine ICP fit + trending sentiment + usage to flag risk/opportunity early.
Weekly executive brief: auto‑compile top risks, expansions, and blockers for the next cycle.
Sales acceleration
Lead enrichment & research: auto‑pull firmographics, technographics, and recent signals; write clean contact summaries.
Pre‑meeting brief & agenda: smart account + participant digest from internal + external data, with a proposed agenda sent to Slack.
Sales→CS handover: convert opportunity trail (notes, emails, calls) into a crisp customer brief + initial success plan.
CS, Sales & Service efficiency
Call transcript summaries: action‑oriented summaries tuned to account context (not just transcript‑level gist).
Ticket risk detection: negative sentiment + “churn cues” trigger owner alerts and playbook steps.
Renewal & deal forecasting assist: agents compile signals that influence probability and timing.
Automated data entry: structured updates from meetings/emails/tickets—fewer empty fields, better history.
These are just some introductory examples - start with looking at which processes you run that matter or cost a lot, and break down what parts or decisions are repetitive enough for automation. There AI can probably help.
Here you can see what our Technical Deployment Specialist Marco uses the MCP server + Claude for:
What you can do now
Fast portfolio visibility
AI‑driven health score: combine ICP fit + trending sentiment + usage to flag risk/opportunity early.
Weekly executive brief: auto‑compile top risks, expansions, and blockers for the next cycle.
Sales acceleration
Lead enrichment & research: auto‑pull firmographics, technographics, and recent signals; write clean contact summaries.
Pre‑meeting brief & agenda: smart account + participant digest from internal + external data, with a proposed agenda sent to Slack.
Sales→CS handover: convert opportunity trail (notes, emails, calls) into a crisp customer brief + initial success plan.
CS, Sales & Service efficiency
Call transcript summaries: action‑oriented summaries tuned to account context (not just transcript‑level gist).
Ticket risk detection: negative sentiment + “churn cues” trigger owner alerts and playbook steps.
Renewal & deal forecasting assist: agents compile signals that influence probability and timing.
Automated data entry: structured updates from meetings/emails/tickets—fewer empty fields, better history.
These are just some introductory examples - start with looking at which processes you run that matter or cost a lot, and break down what parts or decisions are repetitive enough for automation. There AI can probably help.
Here you can see what our Technical Deployment Specialist Marco uses the MCP server + Claude for:
What you can do now
Fast portfolio visibility
AI‑driven health score: combine ICP fit + trending sentiment + usage to flag risk/opportunity early.
Weekly executive brief: auto‑compile top risks, expansions, and blockers for the next cycle.
Sales acceleration
Lead enrichment & research: auto‑pull firmographics, technographics, and recent signals; write clean contact summaries.
Pre‑meeting brief & agenda: smart account + participant digest from internal + external data, with a proposed agenda sent to Slack.
Sales→CS handover: convert opportunity trail (notes, emails, calls) into a crisp customer brief + initial success plan.
CS, Sales & Service efficiency
Call transcript summaries: action‑oriented summaries tuned to account context (not just transcript‑level gist).
Ticket risk detection: negative sentiment + “churn cues” trigger owner alerts and playbook steps.
Renewal & deal forecasting assist: agents compile signals that influence probability and timing.
Automated data entry: structured updates from meetings/emails/tickets—fewer empty fields, better history.
These are just some introductory examples - start with looking at which processes you run that matter or cost a lot, and break down what parts or decisions are repetitive enough for automation. There AI can probably help.
Here you can see what our Technical Deployment Specialist Marco uses the MCP server + Claude for:
A New Dawn
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