The fastest way to build AI agents

Create an agent that pulls roadmap items from {{Notion}} or {{Linear}}, combines them with team capacity, current workload, and historical delivery data, and highlights where the roadmap is overcommitted or misaligned.

Create an agent that pulls product usage data from {{PostHog}} and account data from {{Salesforce}}, detects declining usage trends, flags at risk accounts ahead of renewal dates, and outputs a prioritized list with risk level and recommended next actions in {{Notion}}.

Create an agent that pulls {{Linear}} updates, PR statuses, and release notes, then generates a weekly team update with per person task summaries, posting it to {{Slack}} and saving a full report as a {{Notion}} page.

Every day at 9am, pull a keyword from {{Google Sheets}}, fetch top ranking articles via {{SERP API}}, scrape them with {{Firecrawl}}, analyze themes and structure, add light supporting research, generate a long form SEO optimized article, and save it to a {{Google Doc}} linked back in the original spreadsheet.

Create an agent that analyzes transaction patterns to identify potential fraud. Pull recent transactions from {{Stripe}}. Then build agent with tools that will detect anomalies using rule-based and LLM pattern recognition (e.g., velocity, unusual merchant, location mismatch). Summarize flagged cases in {{Slack}}.

Create an agent that automates “Know Your Customer” (KYC) checks. Look at customer-uploaded documents in {{Hubspot}}. Verify document validity, completeness, and expiry. Flag missing or inconsistent information and recommend follow-up actions. Output a compliance summary and send a report via {{Gmail}}. Send a report to internal {{Slack}} channel (i will provide it).

Create an agent that compiles a weekly summary of each client’s investment portfolio. Pull holdings, performance, and benchmark data from a PDF. Then generate a summary for top performing assets, risk exposure and allocation drift. Using this summary generate a 5 page slide {{Gamma}} presentation. Send the slides to my clients (I'll provide their emails).

Create a contract review agent that parses documents into structured JSON, checks clauses against a checklist, flags missing or risky language, scores and categorizes each issue, and suggests mitigations. Output an executive summary, redline CHANGE FROM / TO edits, negotiation guidance, and save results as a row in {{Google Sheets}}.

Create an agent that reviews uploaded NDAs from a specified {{Google Drive}} folder by extracting key clauses like confidentiality period, exclusions, governing law, and IP ownership, comparing them to a company approved template, assessing risk as Low Medium or High, and sending a short summary to {{Slack}} with a detailed Markdown review.

Create an agent that reviews DPAs or privacy policies, checks required obligations against a compliance checklist, scores compliance, flags gaps, and sends recommendations to {{Slack}} or {{Gmail}}.

Create a prior authorization review agent that takes latest uploaded documents from {{Google Drive}}, extracts text, parses notes and codes, checks coverage against plan criteria, identifies missing items, and outputs a structured JSON summary with determination and recommendations.

Create an agent that checks claim submissions in {{SharePoint}} against payer rules, flags coding errors or duplicates, and recommends fixes or rejections.

Create an agent that turns EHR data and clinical guidelines into a personalized care plan by parsing diagnoses, meds, and labs, then recommending steps, goals, and follow up timing in clinician friendly Markdown for EHR entry.

Create an agent that analyzes a {{Gong}} transcript, extracts objections, and updates the related HubSpot contact using the customer email.

Create an agent that sends a weekly {{HubSpot}} active deals report to {{Gmail}} and {{Slack}} with deal size, last communication, likelihood percent, and next activity date, grouped into Green Yellow Red, flags any deal past its close date as Red, and prompts you to either update the close date or mark it closed lost with a reason.

Create an agent that reviews Closed Lost deals from {{HubSpot}} each week, extracts deal size, loss reason, competitor, and lost stage, identifies recurring patterns like pricing or missing features, and posts a summary to {{Slack}} or {{Notion}} every Friday.

Create an agent that takes a web URL and desired output, extracts key themes, uses {{Web search}} for research, generates the content, and saves the final article in {{Notion}}.

Create a content repurposing agent that takes a webinar transcript, pulls out the main themes, adds supporting stats from light {{Web research}}, and generates three {{LinkedIn}} posts, one recap draft in {{Notion}}, and pings me in {{Slack}} once done.

Create an agent that scans {{HubSpot}} for deals renewing in the next 60 days, scores renewal risk as High Medium or Low using recent communication, usage, and notes, and sends a weekly action focused summary to a user chosen {{Slack}} channel.

Create an agent that detects escalated support tickets, summarizes context, assigns them in {{Linear}}, and posts a summary to a chosen {{Slack}} channel.

Create a support chatbot that classifies messages into Billing, Product Help, Account Management, or Escalation, answers from your knowledge base, and for Escalation notifies a chosen {{Slack}} channel and tells the user a human will follow up.

Build an agent that monitors selected subreddits on {{Reddit}}, filters high engagement posts, and sends formatted summaries to a chosen {{Slack}} channel.