
Diligenceflow automates VC due diligence using four AI agents: Scout extracts internal/external factors, Brief Writer generates IC memos, Journey Mapper builds decision workflows, and Risk Scorer calculates dimensional risk (0-100). Features include stage-aware analysis, alternative data integration, confidence labeling (CONFIRMED vs INFERRED), and institutional-ready exports. Perfect for deal screening, IC prep, and portfolio analysis. Processes 2-3 minutes per deal using Claude Haiku 4.5 (~$0.15 cost). Current MVP supports single users; enterprise scaling roadmap includes database, SSO, REST API, and SOC2 compliance.
31 May 2026

Enterprises are deploying AI agents that autonomously access Jira, edit tickets, change priorities, and modify sensitive project data — while security teams have zero visibility. A single misconfigured agent edited a CONFIDENTIAL payroll credential ticket across 6 fields in under 7 minutes. AgentGuard caught it, blocked every action, and generated an audit report in real time. AgentGuard is a runtime governance platform that sits between AI agents and enterprise systems. It monitors every Jira action in real time, classifies risk, detects AI-originated behavior, and produces audit trails a compliance officer can actually sign. Four Governance Layers: Real-Time Action Monitoring - every Jira action (CREATE, EDIT, ASSIGN, DELETE) is captured via REST API with full changelog context. Actor, timestamp, field, old value, new value all logged. Multi-Signal AI Detection - identifies whether actions came from humans, AI agents (Claude, GPT), or Atlassian Intelligence using five signals: content patterns, Atlassian template structure, API origin behavior, velocity detection (inhuman speed), and structural similarity across tickets. Rule-Based Policy Engine - DELETE on compliance tickets = BLOCKED. Edits to CONFIDENTIAL content = BLOCKED. CRITICAL priority escalations = FLAGGED. Every decision is transparent and explainable — not a black box. Prompt Inspection via Lobster Trap - Veea's deep prompt inspection layer analyzes AI-generated ticket content for injection patterns, credential exposure, and data exfiltration signals. Declared versus detected intent is shown side by side. Every action shown in AgentGuard comes from a live Jira project. Claude Haiku autonomously created tickets tagged [AI-GENERATED]. Atlassian Intelligence rewrote a CONFIDENTIAL payroll ticket. AgentGuard detected both — real data, real governance, real audit trail.
19 May 2026