An energy trading desk managing a $800M annual portfolio was using spreadsheet-based risk management and manual trade execution. Market data arrived on 15-second delays, causing missed opportunities in volatile real-time markets.

VaR calculations ran overnight, meaning traders operated without current risk visibility. Settlement reconciliation required 2 FTEs full-time. FERC compliance reporting consumed 1 week per month, and the desk had received a warning for a reporting discrepancy.

The desk needed real-time market intelligence, automated execution, continuous risk monitoring, and automated compliance.

The Solution

A 7-agent trading desk that analyzes markets, executes trades, manages risk, and ensures compliance

Vijan.AI deployed 7 agents. The Market Data Collector streams real-time prices from exchanges and bilateral markets. The Forecaster predicts short-term price movements using weather, demand, and supply signals. The Position Manager tracks portfolio exposure across all markets. The Risk Assessor runs continuous VaR, stress tests, and scenario analysis. The Execution agent places trades via exchange APIs with optimal timing. The Settlement agent reconciles completed transactions automatically. The Compliance agent logs all trading activity for FERC reporting with full audit trails.

Autonomous Agents

How each agent reasons, decides, and acts

Step 1 · Trading

Energy Trading Agent

Wholesale Market Trading & Dispatch

Executes day-ahead and real-time trades on ISO markets to balance generation and load, autonomously bidding assets, hedging price risk, and capturing arbitrage opportunities.

Input

Load forecasts, generation schedules, ISO LMPs, contract positions

Output

Trade orders, bid stacks, P&L positions, settlement data

Calls ISO market API for day-ahead and real-time LMP and ancillary service prices
Calls contract database to retrieve bilateral hedges and capacity obligations
Autonomous decision: bid generation, buy shortfall, or hold for real-time pricing
Routes trade confirmations to Broker and PPA Manager for reconciliation

Step 2 · Brokerage

Energy Broker Agent

Energy Brokerage & RFQ Management

Solicits and compares quotes from suppliers and brokers for corporate energy procurement, autonomously selecting lowest-cost offers and executing forward purchase agreements.

Input

Load forecasts, supplier RFPs, broker quotes, forward curves

Output

Quote comparisons, contract awards, broker confirmations

Calls broker API to submit RFQs and collect competitive bids
Calls RFQ portal to compare offers by price, term, and counterparty credit
Autonomous decision: accept low bid, negotiate terms, or defer to next RFQ round
Routes awarded contracts to PPA Manager and Cost Allocator

Step 3 · PPA

PPA Deal Manager

Power Purchase Agreement Structuring

Negotiates long-term PPAs with renewable developers and corporate off-takers, autonomously modeling economics, tracking RECs, and managing contract amendments.

Input

PPA term sheets, pricing models, REC values, counterparty credit

Output

Signed PPAs, REC tracking, contract amendments, deal valuations

Calls PPA database to retrieve active contracts, pricing, and delivery schedules
Calls financial model to value contracts using forward curves and REC pricing
Autonomous decision: approve deal, request price adjustments, or decline offer
Routes PPA economics to Utility Rate Optimizer for cost recovery planning

Step 4 · Utility Rates

Utility Rate Optimizer

Corporate Utility Rate Optimization

Analyzes customer load profiles to recommend optimal utility tariffs, autonomously switching customers to time-of-use or demand response rates to minimize bills.

Input

Usage profiles, tariff schedules, DR programs, billing history

Output

Tariff recommendations, rate switch orders, savings estimates

Calls tariff database to retrieve available rate plans and eligibility rules
Calls usage API to model bill impacts under TOU, demand, and flat rate structures
Autonomous decision: recommend rate switch, enroll in DR, or maintain current plan
Routes savings opportunities to Renewable Sales for bundled solar+rate offers

Step 5 · Renewables

Renewable Sales Agent

Renewable Energy Sales & Customer Acquisition

Generates proposals for commercial solar and wind projects, autonomously calculating ROI, financing options, and REC revenue to close deals with corporate customers.

Input

Site assessments, customer usage, incentive programs, financing rates

Output

Proposals, ROI models, financing options, signed contracts

Calls CRM to identify high-usage commercial prospects and engagement history
Calls proposal generator to create customized solar quotes with incentive stacking
Autonomous decision: approve financing, escalate to sales team, or defer pending incentives
Routes signed deals to Cost Allocator for revenue and incentive tracking

Step 6 · Cost Allocation

Cost Allocation Agent

Revenue & Cost Reconciliation

Allocates trading revenue, PPA costs, and renewable sales across business units, autonomously generating P&L statements and FERC-compliant financial reports.

Input

Trade settlements, PPA invoices, renewable revenue, FERC account codes

Output

P&L statements, FERC reports, audit trails

Calls general ledger to post trading P&L and PPA costs by account code
Calls FERC API to validate account classifications for wholesale and retail transactions
Autonomous decision: allocate costs by usage, capacity, or regulatory formula
Routes financial summaries to Rate Case Analyst for regulatory filings

Step 7 · Rate Case

Rate Case Analyst

Regulatory Reporting & Rate Recovery

Compiles trading revenue and PPA costs into rate case filings, autonomously generating testimony and tracking PUC approvals for cost recovery and rate adjustments.

Input

Allocated costs, trading P&L, PPA expenses, PUC dockets

Output

Rate case filings, testimony exhibits, cost recovery orders

Calls PUC portal to retrieve filing deadlines and rate case schedules
Calls rate modeling tool to calculate revenue requirements and tariff impacts
Autonomous decision: file rate case, request interim rates, or defer to next cycle
Routes approved cost recovery to finance for revenue recognition and tariff updates

Results

Measurable impact within 90 days of deployment

20%

Better Trading Margins

Trading margins improved from 4.2% to 5.04% through better price forecasting and optimal execution timing.

$16M

Incremental Revenue

Annual incremental trading revenue from improved margins and reduced missed opportunities.

Real-time

Risk Visibility

VaR and portfolio exposure updated continuously vs. overnight batch. Traders have instant risk awareness.

100%

FERC Compliance

Automated FERC reporting with zero discrepancies. Monthly reporting reduced from 1 week to 2 hours.

Implementation

From pilot to production in 12 weeks

Week 1-4

Agent Design & Tool Integration

Defined agent capabilities, connected ML model, rules engine, graph DB, and chargeback API tools. Configured orchestrator routing logic.

Week 5-8

Shadow Mode & Autonomous Tuning

Agents ran in shadow mode on 10% of transactions. Tuned decision thresholds, tool call parameters, and feedback loop retraining frequency.

Week 9-12

Full Autonomous Deployment

Production rollout across all channels. Agents operating fully autonomously with human-in-the-loop for critical escalations only.

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