01
The average hides the opportunity
Scarcity, congestion, negative prices, and ramps concentrate value in a small number of intervals. Point forecasts flatten the outcomes that matter most.
Agentic bidding + market operations for battery storage
Observe the market.Price the tail.Bid the curve.
An AI orchestration layer coordinates data, models, market rules, approvals, bidding, and settlement around a purpose-built quantitative engine. You choose what runs automatically, what requires approval, and what stays advisory.
ERCOTCAISODecision-time auditable
MARKET OPERATIONS
SYSTEM ACTIVEDEFAULT DECISION AUTHORITY
Quantitative engine
FORECASTDistribution
VALUEState of charge
OUTPUTOffer curve
05:42:11Market data validated
05:42:14Scenario paths generated
05:42:18Offer curve verified
The operating problem
A battery needs more than a forecast.
Storage is a sequence of linked decisions made under uncertainty. The commercial edge comes from coordinating the entire loop before each deadline, not optimizing one step in isolation.
02
Every action changes the next one
Awards, ancillary commitments, and real-time moves all compete for the same power, capacity, and state of charge. A static schedule cannot keep up.
03
The workflow is fragmented
Data, models, telemetry, market rules, risk limits, approvals, and settlement move on different cadences. Manual handoffs add delay when consistency matters most.
04
Hindsight rewards weak strategies
Perfect-foresight schedules use prices that were unknown when bids were due. Tradable performance must be measured point in time, with every decision attributable.
SLS / THE RESPONSE
The missing layer is coordination.
SLS watches the operating environment, invokes the quantitative engine, verifies its output, routes each action through your authority policy, and keeps monitoring what happens next.
System architecture
AI orchestration around a quantitative authority.
The orchestrator coordinates the full market-operations loop. The engine remains responsible for bid prices, quantities, and physical feasibility.
Central guardrailThe agent cannot bypass asset constraints or manufacture a price. Authorized overrides are recorded with the decision.
Three coordinated layers
Built to decide. Designed to be governed.
Language models are useful coordinators, not pricing engines. SLS separates workflow intelligence, quantitative decision authority, and operating control by design.
01 / ORCHESTRATE
Agentic market operations
The orchestrator checks data freshness, watches rules and deadlines, plans the due workflows, invokes each tool, verifies the result, and routes the next action. It connects work that normally lives across analysts, traders, operators, and disconnected systems.
- Observe + plan
- Invoke + verify
- Act + monitor
02 / DECIDE
Quantitative bidding engine
Market-specific probability distributions feed state-of-charge valuation and energy plus ancillary-service co-optimization. The engine produces feasible price-quantity curves and rolling real-time decisions around awards and obligations.
- Forecast distributions
- Value stored energy
- Construct offers
03 / CONTROL
Risk and operating controls
Authority is explicit and configurable by environment, asset, and workflow. Exposure limits, deliverability constraints, approval gates, model promotion rules, kill switches, and recorded human overrides stay attached to every decision.
- Configurable authority
- Exposure limits
- Complete audit trail
The operating loop
Always watching. Never improvising the bid.
The agent coordinates the work. The quantitative engine remains the default authority for prices, quantities, and feasibility.
01
Observe
Ingest market and asset data. Check freshness, model health, telemetry, positions, P&L, risk limits, and market-rule changes.
02
Plan
Determine what is due, which dependencies are missing, and which exceptions need attention before the next market deadline.
03
Invoke + verify
Run ingestion, training, forecasting, optimization, reporting, and settlement tools. Verify each result before it can move downstream.
04
Act
Route decisions automatically, through an approval gate, or as advice. Record the action, its rationale, and any authorized override.
05
Monitor + learn
Continue watching execution and asset state. Reconcile settlement, attribute performance, alert operators, and retrain only when defined gates are met.
Two deployment models
Keep the desk. Or deploy the desk.
Start with the operating model that matches your team today. Both paths use the same engine, controls, decision records, and market-specific workflows.
Intelligent trading system license
For teams keeping commercial operations in house
Deploy the orchestrator and quantitative engine into a customer-hosted or isolated SLS-hosted environment. Your team retains its market relationships and operating control while SLS coordinates the repeatable data, model, decision, and reporting work.
- Automatic, approval-gated, or advisory workflows
- Market-specific forecasts and optimized offers
- Model operations, alerts, and attribution
- Integration designed around your existing operating stack
Full trading-as-a-service
For owners seeking a turnkey commercial operation
SLS manages the operating workflow from ingestion through settlement and coordinates bid exchange with the asset's QSE in ERCOT or Scheduling Coordinator in CAISO. Authority, exceptions, and risk limits remain explicit and visible to the customer.
- Complete managed market workflow
- Energy and ancillary-service co-optimization
- Rule monitoring and exception management
- Decision-level revenue and settlement attribution
Why SLS
The system is differentiated by what it refuses to blur.
01
The whole loop, coordinated
Data, models, rules, approvals, bids, monitoring, settlement, and learning operate as one traceable workflow.
02
AI grounded in math
The orchestrator does not invent bid prices. The battery engine is the default authority for price, quantity, and feasibility.
03
Control is configurable
Choose automatic, approval-gated, or advisory operation by workflow. Authorized people can stop or override action.
04
Evidence stays attached
Trace each decision from information cutoff and model version through constraints, approval, offer, alerts, and settlement.
Start without changing live operations
Prove the loop in shadow mode.
Run SLS beside your current strategy for 30 days. We produce decision-time forecasts, offers, approvals, alerts, and attribution without submitting a live bid, then compare results on agreed assumptions.
Design a shadow-mode pilot30 daysParallel operating window
No live bidsObserve before authority
Point in timeMeasured without hindsight
Build the operating case
Bring us one asset and one market.
Tell us how the asset operates and how decisions move today. We will map a shadow-mode pilot around your market representative, authority policy, and acceptance criteria.
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