Architecture Overview · Enterprise AI Delivery

Pre-Sales Intelligence Research Agent

Agentic research system that takes a company name and produces a 13-section intelligence briefing in ~8 minutes by orchestrating 5 live data tools — LinkedIn, financials, news, domain analysis, and executive tracking.

Enterprise Sales ToolAzure AI Foundry · Claude0 Manual Steps

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Input
Company Name + Mode
Single prospect identifier (e.g., "Acme Corp") + optional mode selection: PE Intelligence (general) or RXT Seller Diligence (Rackspace-specific)
Natural Language Trigger
Agentic Research Pipeline — 13 report sections
Step 1
Tool Orchestration
5 live tools: LinkedIn search, financial data, news aggregation, domain analysis, executive tracking
›
Step 2
Stakeholder Mapping
Economic buyer, technical champion, procurement authority — identified from live data
›
Step 3
Opportunity Ranking
Top 3 Focus Areas with evidence, confidence score, and entry point conversation starters
›
Step 4
Report Assembly
13-section briefing with full citation index and hyperlinked source verification
🎯
Anti-Dithering Design — Agent Rules & Output Constraints
Explicit rules prevent the agent from stalling or hedging. Output is structured for internal seller prep — never for sharing with prospects. All claims are linked to live-fetched sources.
5 live data tools2 agent modes4 news sourcesAll claims sourcedAnti-dithering rulesSeller-aligned output
Output A
13-Section Briefing
Complete technology diligence report: company overview, tech stack, cloud spend signals, exec team, open reqs, news, regulatory exposure, and Rackspace entry points
~8 min generation
Output B
Top 3 Focus Areas + Citation Index
Ranked opportunities with evidence chains. Every claim hyperlinked to source. Stakeholder map with decision maker profiles
0 manual clicks
13
Report sections
5
Live data tools
2
Agent modes
~8m
Generation time
StackAzure AI FoundryClaude with Tool UseLinkedIn API10-K filingsNews APIsBM25 searchLLM ranking