Agentic Sales & Marketing is a multi-agent AI system built on LangGraph that automates the full B2B sales pipeline for IT services companies. You configure it once with your company profile, pricing, case studies, and a target industry — then the system discovers leads, researches each one, scores it against your ideal customer profile, analyzes the competitive landscape, generates personalized outreach and proposals, and writes everything to Google Sheets. The system is designed for IT services and AI automation companies looking to scale outbound sales without manual research overhead.Documentation Index
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Key features
Lead discovery
Web search-powered discovery of target companies based on your industry, requirements, and client job description file.
Lead research
Deep research on each discovered company: website scraping, LinkedIn decision-maker lookup, and company intelligence gathering.
ICP matching
Score each lead against your configured ideal customer profile and filter out poor fits before investing time in outreach.
Competitor analysis
Map the competitive landscape for each deal and surface positioning strategies tailored to the lead’s existing vendors.
Outreach generation
Generate personalized cold emails, LinkedIn messages, follow-up sequences, and call pitches for every qualified lead.
Proposal generation
Produce structured IT services proposals with scope, implementation plans, and pricing drawn from your sales deck.
CRM update
Automatically write lead details, research summaries, outreach content, and next steps to your Google Sheet.
Agent pipeline
The workflow runs as a deterministic LangGraph pipeline. A supervisor agent orchestrates a queue of discovered leads, routing each one through the same sequential chain of specialized agents.Lead discovery
The discovery agent is the entry point. It searches the web for companies matching your
target_industry and client_requirements, then builds a queue of candidate leads stored in discovered_leads.Supervisor routing
The supervisor inspects the lead queue. For each unprocessed lead it routes to
lead_research_agent. When the queue is empty, it sends the graph to END.Research and qualification
The lead research agent gathers intelligence on the active lead. The ICP matching agent then scores it against
ideal_customer_profile and records the analysis in icp_analysis.Competitive intelligence
The competitor analysis agent uses
competitors_data and the lead’s profile to map competing vendors and identify differentiation opportunities.Content generation
The outreach generation agent writes personalized messaging using the lead research, ICP score, and your
sender_name. The proposal generation agent drafts a structured proposal drawing from sales_deck_text, pricing_data, and case_studies.The system uses LM Studio running locally with the gemma-3-4b-it model by default. You must have LM Studio installed and the model loaded before running
main.py. The LLM client connects to http://localhost:1234/v1. See Configure the sales workflow state and LLM for details.