Gemini
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Google Gemini provides the reasoning power of advanced large language models, while Planhat provides the customer context and workflow orchestration required for execution. By connecting Gemini to Planhat’s Automation engine, teams transform unstructured customer conversations into actionable records and automated follow-through directly inside their system of record. Use dedicated AI steps to analyze call outcomes, identify early risk, and generate operational handovers based on the latest account data.
Unlock the power of Gemini with planhat
Improve net revenue retention
Protect recurring revenue by identifying early churn signals within unstructured data. Planhat uses Gemini to analyze email threads and call transcripts for subtle sentiment shifts, allowing commercial teams to execute proactive retention plays before qualitative friction impacts quantitative renewal targets.
Shorten time to value
Compress implementation timelines by automating the transition from sales to implementation. Gemini synthesizes months of pre-sale correspondence and call recordings the moment a deal closes, instantly generating structured handover notes that allow onboarding teams to skip manual discovery.
Increase process governance
Standardize AI execution across the commercial organization by confining model reasoning to rule-based Automation steps. Using Gemini within Planhat’s "Use AI" framework ensures that data updates are governed, predictable, and available as structured JSON for immediate use in record updates or branching logic.
Improve commercial predictability
Base revenue projections on objective behavioral evidence rather than subjective manual entries. Planhat leverages Gemini to reason over account interactions and objectives, producing consistent executive summaries that provide leadership with greater visibility into the true health of renewals and expansions.
how it works
Flow & configuration
Secure authentication via App Center
Authorized administrators link Planhat to your Google Gemini account through the Custom Connections area in the App Center. This "bring-your-own-LLM" model ensures your data remains subject to your own enterprise security and compliance agreements while allowing Planhat to invoke your specific model endpoints.
Define prompt and chat endpoints
Establish the connection logic by configuring prompt or chat endpoints that define how Planhat communicates with specific Gemini models, such as Gemini 1.5 Flash. This setup allows Planhat to establish the necessary instructions and authorization headers for secure, context-aware model invocation.
Embed the "Use AI" step in Automations
Add a dedicated AI step to any Planhat Custom Automation to trigger model requests at specific lifecycle moments, such as a status change or a closed deal. Planhat sends the defined prompt along with real-time customer data, including email history and call transcripts, to Gemini for processing.
Map structured JSON or narrative outputs
Define how the model response is handled by requesting either unstructured narrative text for notes or structured JSON for branching logic. Structured results allow the Automation to update specific records, enrich Company data, or branch the workflow to notify owners via Slack based on the AI's reasoning.
Execute operational follow-through
Planhat turns the model response into immediate action, such as creating a Customer Success handover note or updating a risk label. This ensures that AI reasoning is recorded directly into the customer record, allowing teams to act on insights without manual data entry or manual review of long conversation chains.
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