Digital & AI Solutions

Digital Solutions for Commodity and Energy Trading

Understand P&L, close books faster, free up working capital and reduce manual work in trading operations

moving car city blue

AI for CTRM and ETRM Platforms

Commodity trading teams lose margin in the gaps between systems. Demurrage spotted too late, breaks found at month end, forecasts stale before they are finished.

capSpire’s Digital Solutions close those gaps on the ETRM platform you already own: five layers of proprietary trading platform accelerators, spanning connectors, an AI-ready data lake, data services, agents, and apps Model Context Protocol (MCP) enabled. Where you need something the suite does not cover, our forward deployed engineering pods build it inside your environment, taking AI from pilot to production.

Where AI Actually Delivers in Trading Operations

Reconcile continuously, not monthly

Match nominations, surface only exceptions

Refresh in-month forecasts as activity changes

Detect anomalies across trades, volumes and tolerances

Query position, exposure and P&L in natural language

Accelerate flash P&L and financial close

The capSpire Digital Solutions Suite

Each layer stands alone. Take one, or all five.

Connectors: ETRM integration you do not have to build and maintain

Connectors built internally often become a maintenance commitment at the next upgrade. capSpire’s are proven in production across sources including Platts, Geometrics, T4, SAP and Zema, connecting in and out of the ETRM through a direct C/ETRM connection or an MCP server. 

Data Lake: one version of the numbers, for reporting and AI alike

Ask two teams for the same P&L number and the answers can differ. The capSpire ETRM data lake holds all trading platform data as an AI-ready schema for reporting and Gen AI, across bronze, silver and gold layers, on the enterprise data platform you already run such as Snowflake, Databricks or Microsoft Azure Data Lake Storage (ADLS).

Data Services: the risk and P&L reporting your platform rarely provides

Risk Reporting delivers the mark to market (MtM), profit and loss (P&L) and P&L contribution numbers most deployments struggle to generate, without funding a reporting project first. Trading Data Hub puts governed trading data within reach of the teams that need it. Both sit on the data lake and arrive supported.

Agents: routine work handled in the background

Reconciliation does not have to wait for month end. AI agents run continuously on the data lake, automating technical and business tasks and surfacing the breaks that need attention, each traceable to source. capSpire’s ready to use agent library gives your team a starting point rather than a build from scratch. Where the library does not cover a use case, an FDE pod builds the agent you need, tested against your data and controls.

Apps: cost avoided closer to where it arises

Logistics Intelligence catches nomination exceptions while demurrage, penalty and working capital cost can still be avoided, and keeps the in month forecast current. Quick Trade Entry reduces capture time and Customer360 consolidates the counterparty view. All connect directly to the trading system and are MCP enabled, so AI assistants and agents reach trading context through a standard interface.

Your Trading Technology Landscape

A C/ETRM platform rarely holds the whole picture. Market connectivity, pricing and valuation, risk engines, logistics, settlement and recon, accounting and ERP, metering and weather each hold a piece.

The suite connects that landscape and surfaces it through data services, agents and apps, out to SharePoint, Copilot, orchestration and gateways.

Data Activation and Data Enablement

Data readiness comes first. AI value depends less on the model than on whether your trading data is governed well enough to query safely. capSpire makes the right data accessible through data activation and data enablement: process, governance and secure access, so risk, finance and audit can trust an automated number.

Forward Deployed Engineering

Most trading organizations already have AI. Few have it working inside their C/ETRM landscape. Our forward deployed engineering (FDE) pods pair C/ETRM domain experts with senior AI engineers, embedded in your environment. They build, ship and support agents against your real data, workflows and controls. We work in four steps: Assess, Enable, Build and Scale.

Digital Factory

Digital Factory is our custom development practice, using AI to build and maintain code faster, covering new repositories, legacy reverse engineering, language migrations and support for code you already run.

Digital, Data & AI Advisory

Our advisory work covers technical audits and platform maturity assessments, AI roadmaps and implementation, and system modernization across data architecture and cloud enablement. It also extends to the analytics and tools that follow: economic P&L, attribution and value at risk, supply, demand and in month forecasting with scenario testing, and End of Day as a Service for risk and margin reporting.

WHY CHOOSE CAPSPIRE

capSpire is driving innovation in digital, data and AI accelerators for commodity trading participants. No migration, no middleware, no separate platform license, and nothing an upgrade can overwrite. Every automated number traces back to source and reconciles against official reporting. Let us help you implement your digital strategy.
Speak with a capSpire Digital and AI Expert

Frequently ASKED QUESTIONS

How can AI help us get more from our CTRM or ETRM platform?
AI pays back fastest on repetitive, rule based work that is still done by hand. Automating it shortens the financial close, reduces penalty and working capital cost, and releases people from routine checking. All of it depends on modeled, governed trading data, which is usually the first project rather than the last.
Operational ones, ahead of predictive ones. Reconciliation, nomination exception handling and in-month forecasting tend to return value within a quarter, because the rules already exist and only the execution is manual. Price forecasting attracts more attention but sits further out, and rests on the same data model.
Ask how one specific P&L number is produced today. If the answer is a single purpose extract and a spreadsheet, an agent would inherit every gap in it. If it is a documented model that risk and finance already rely on, it can carry automation.
A range of proprietary trading platform accelerators for commodity and energy trading, across five layers. Connectors provide connectivity in and out of the ETRM. The Data Lake holds an AI-ready ETRM data schema. Data Services such as Risk Reporting and Trading Data Hub sit on top of that data lake, as do Agents that automate operational tasks. Apps connect directly to the trading system and are Model Context Protocol (MCP) enabled. Take the layers together or separately.
Prebuilt integrations that move data in and out of the ETRM, covering sources including Platts, Geometrics, T4, SAP and Zema. They run over a direct C/ETRM connection or a Model Context Protocol (MCP) server. They are supported components rather than bespoke code, so you configure them instead of building them, and the maintenance no longer falls to you at every upgrade.
Either works on day one. The question is year three: who maintains it through platform upgrades and market data changes once the person who wrote it has left. capSpire has already productized the connectors, the data model, the data services and the agent library, so each arrives supported rather than slowly going stale.
A data store built specifically around a trading platform’s schema, holding trade, position and risk data in a business ready structure rather than raw tables. capSpire’s version can land on your existing enterprise data platform, so reporting, analytics and AI all read from one governed source instead of competing extracts.
Three things: the model is documented, the layers are separated so raw, cleansed and business ready data are distinguishable, and lineage is intact so any figure can be traced back. Together they mean an AI query and your official reporting return the same answer.
Yes, and they work together. Those platforms bring storage and compute, but they do not carry any knowledge of your trading platform’s data model. Interpreting the application logic, mapping it and keeping it current through upgrades is the actual work. capSpire supplies that model and writes into the environment you have already licensed.
Ready made data products that run on the data lake, so reporting arrives as a supported capability rather than a project. Risk Reporting handles the risk and P&L figures that trading platforms rarely produce directly. Trading Data Hub makes governed trading data available across teams and tools.
Software, sometimes described as agentic AI, that reads a governed trading data set and takes over a task a person does by hand: reconciling systems, testing volumes against tolerances, raising exceptions. Running on modeled data with clear lineage is what makes its output auditable rather than merely fast.
Yes. The agent library means automation starts from proven components rather than a blank page, with reconciliation the most established. Agents sit on top of the data lake and can automate or optimize both technical and business tasks.
Reconciliation automates well because the rules are already written and only the execution is manual. capSpire’s reconciliation agent runs continuously on governed data, compares systems and raises only the breaks that need a person. Breaks surface while they are still inexpensive to resolve, and each one traces back to source.
MCP, the Model Context Protocol, is an open standard for connecting AI systems to external tools and data. An MCP server gives assistants and agents one standard route into trading platform context, replacing a bespoke integration per tool per system. capSpire Apps are MCP enabled, and Connectors support an MCP server connection.
Two routes. A direct connection reads the platform through native interfaces, which suits apps extending platform functionality. A Model Context Protocol (MCP) server exposes platform context to AI assistants and agents through that open standard. Most organizations run both, over a data lake holding the governed model underneath.
Nomination management software for commodity and energy trading, and an app within the Digital Solutions Suite. It automates daily nomination entry, tracking and in month forecasting, connects straight to the trading platform, matches nominations against live positions and flags exceptions early enough to avoid demurrage, penalty and working capital cost. Built for ETRM users still running nominations in spreadsheets.
They were designed for trade capture and risk processing, not physical scheduling. So scheduling teams keep nominations in spreadsheets beside the platform. The result is two sources of truth, manual reconciliation, version control problems, and a forecast that is out of date by the time it is circulated.
Platform schemas run to thousands of tables, and the logic turning those tables into a trade, a position or a P&L number lives in the application layer rather than the database. Usable data means interpreting that logic and mapping it to a business model. Most organizations settle for targeted extracts instead.
No, because the two are complementary. Whatever a vendor ships performs according to the data model beneath it, and it will not reach processes outside the platform. An AI-ready model improves reporting now and readies the ground for vendor features later.
Your organization. capSpire builds a governed data set with clear lineage, so any automated number traces to source and reconciles against official reporting. Paired with data activation and enablement covering process, governance and secure access, that traceability is what risk, finance and audit sign off against.
Neither. The suite adds capability to the platform you already own, with no migration program. Everything attaches through supported interfaces, so an upgrade finds nothing of ours to overwrite. That is the difference from custom modification, which the next upgrade can reverse.

capSpire builds software as well as advising. Most firms in this market diagnose platform gaps and hand over a recommendation. capSpire has engineered proprietary accelerators that close those gaps and runs them in client production environments today, maintained by the same consultants who work inside these platforms. Furthermore, our FDE pods build inside your environment and stay accountable for whether it works.

capSpire has decades of experience across market leading ETRM and CTRM platforms in energy, commodities and capital markets, including RightAngle, Openlink, Allegro, Aspect and TriplePoint.
Data Lake and Data Services sit with data architects, IT architects and heads of data or technology, with risk and finance as the reporting users. Apps such as Logistics Intelligence belong to scheduling, logistics and inventory teams, with IT on deployment. Agents are sponsored by whichever operations function they automate. FDE engagements need a business owner who works alongside the pod.
Embedded pods of C/ETRM domain leads and senior AI engineers who build, ship and support AI agents inside your environment. All AI-generated code is reviewed by senior engineers and tested automatically.

It suits teams whose C/ETRM landscape is live and changing, who can provide a business owner to work alongside the pod, and who want running software rather than a roadmap.