AI Agentic Demand Forecasting System
Deploys 9 specialized AI agents that collaboratively analyze regulatory signals, market trends, client intelligence, and internal capacity to generate 30/60/90-day demand forecasts by practice area. Produces executive summaries, technical analysis, and business recommendations with autonomous action capabilities for recruitment, client outreach, and talent repositioning.
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Demand Forecasting Dashboard - 30/60/90-day forecast overview
Market Intelligence - Regulatory and competitor analysis
Talent Strategy - Capacity planning and repositioning recommendations
Client Intelligence - Proactive opportunity identification
AI Agents
Specialized autonomous agents working in coordination
Workflow Orchestrator
Multi-agent forecasting workflows require coordination of parallel execution, dependency management, state synchronization, and result aggregation across specialized agents.
Core Logic
Coordinates the 9-step workflow: Initialize Context, Market Analysis, Demand Forecasting, Client Intelligence, Talent Strategy, Risk Assessment, Compliance Check, Recommendations, and Action Preparation. Manages agent-to-agent communication, creates checkpoints for resumability, and aggregates contributions into final output. Uses GPT-4o with temperature 0.5.
Demand Forecaster
Predicting talent demand requires analyzing historical patterns, market signals, and regulatory calendars to generate accurate forecasts with confidence intervals.
Core Logic
Generates 30/60/90-day demand forecasts by practice area using GPT-4 Turbo + ARIMA ensemble models. Analyzes consultant database, calculates capacity gaps, retrieves knowledge documents for context, and identifies demand drivers (regulatory deadlines, client events, market trends). Outputs forecasts with trend classification (surge/growth/stable/decline) and confidence scores. Tools: query_consultant_db, calculate_capacity, retrieve_knowledge_docs.
Market Analyst
Demand forecasts need market context including regulatory changes, competitive dynamics, and economic signals that affect legal services demand.
Core Logic
Analyzes market signals across regulatory (EU AI Act, MiCA, CSRD), economic (M&A activity, PE deployment), and competitive (LOD, Vario, Axiom moves) dimensions. Tracks search trends, news sentiment, and industry indicators. Uses Claude 3 Opus for sophisticated signal interpretation. Tools: fetch_regulatory_updates, analyze_market_trends, fetch_competitor_intel.
Talent Strategist
Forecasted demand must be translated into actionable workforce plans including recruitment, repositioning, and training strategies.
Core Logic
Develops comprehensive talent strategies from forecasts. Identifies critical capacity gaps, recommends external recruitment with sourcing channels, identifies repositioning opportunities (e.g., Employment Law to AI Compliance with 72% skill adjacency), and designs upskilling programs. Uses Claude 3 Sonnet. Tools: query_consultant_db, calculate_capacity.
Risk Assessor
Forecasts carry uncertainty that must be quantified and communicated. Decision-makers need to understand confidence levels and risk factors.
Core Logic
Evaluates forecast confidence by component (demand forecasts, market signals, capacity analysis). Identifies uncertainty factors (regulatory timeline shifts, competitor actions, economic conditions), calculates historical accuracy metrics, and recommends mitigation strategies. Calibrates confidence intervals. Uses GPT-4 Turbo. Tools: retrieve_knowledge_docs.
Recommendation Engine
Analysis outputs need to be synthesized into prioritized, actionable recommendations with clear implementation timelines.
Core Logic
Synthesizes insights from all agents into prioritized investment recommendations (recruitment, repositioning, training, client outreach). Generates quick wins with effort/impact assessment, creates multi-view outputs (Executive Summary, Technical Analysis, Business Recommendations), and prepares action items for execution. Uses GPT-4o. Tools: predict_client_needs, query_client_crm.
Client Intelligence Agent
Waiting for clients to articulate needs means missing revenue opportunities. Proactive identification of client needs enables first-mover advantage.
Core Logic
Proactively predicts client needs using engagement signals, industry events, and predictive analytics. Analyzes CRM data, identifies high-probability opportunities (e.g., TechCorp Global 89% probability of EU AI Act need), recommends outreach actions with timing and RM assignments. Tracks engagement scores and churn risk. Uses GPT-4o. Tools: query_client_crm, predict_client_needs, analyze_engagement_signals.
Compliance Checker
Recommendations must comply with regulatory requirements and internal policies. Compliance verification prevents regulatory exposure and reputational risk.
Core Logic
Verifies regulatory compliance for all recommendations including EU AI Act requirements, GDPR/UK GDPR, professional conduct rules, conflict checks, and PI insurance verification. Reviews recommended consultant deployments, identifies compliance findings by severity, and clears recommendations for execution. Uses Claude 3 Opus for complex regulatory reasoning. Tools: fetch_regulatory_updates, check_compliance_rules, validate_recommendations.
Action Executor
Approved recommendations require execution across multiple systems (recruitment platforms, CRM, training systems, calendars). Manual execution is slow and error-prone.
Core Logic
Prepares and executes autonomous actions based on approved recommendations. Handles recruitment campaigns (job postings, headhunter activation, candidate outreach), client outreach (personalized briefs, meeting requests), training programs (enrollment, scheduling), and compliance updates. Supports human-in-the-loop approval with auto-execute for low-risk actions. Uses GPT-4 Turbo. Tools: execute_workflow, send_notifications, generate_reports, schedule_meetings.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization