Gravitas ETRM - trade to reportable risk, in one governed system

Traditional ETRM systems are expensive to license, slow to implement and painful to change. A single new product, a new hub or a regulatory tweak can turn into a multi-quarter change request, so desks route around the core in spreadsheets and side databases that nobody governs.

That fragmentation is where risk hides. When positions, curves and P&L live in three different places, the numbers reconcile late or not at all, month-end becomes a fire drill, and the risk team spends more time assembling data than analysing it.

Renewables, PPAs, flexibility products, batteries and carbon rarely fit the original data model of a legacy platform. They were bolted on years after the core was designed, so they sit outside it, and the very products that are growing fastest are the ones the system supports worst.

Upgrades compound the problem. Because customisation is deep and undocumented, every version bump is a project in itself, which means most installations run years behind, carrying known defects and missing the capabilities a modern desk now takes for granted.

Energy markets are being reshaped faster than legacy trading systems can follow. Renewables, PPAs, flexibility products, batteries and carbon have moved from the margins to the centre of many portfolios, and they bring new curve shapes, new optionality and new physical constraints that the data models of a decade ago were never designed to hold.

At the same time volatility has become the norm rather than the exception. Desks need to see risk in real time, price new structures quickly and prove control to regulators, all while margins are under pressure and the appetite for another multi-year, multi-million platform programme has evaporated. The gap between what the market now demands and what rigid legacy stacks can deliver is exactly the gap Gravitas is built to close.

Our vision is to reimagine trading and risk with a platform that is fast to deploy, easy to extend and intelligent by design, so trading houses, utilities and financial institutions can thrive in volatile, low-carbon markets. The mission that follows from it is concrete: unify trading, risk, operations and finance on a single data foundation, enabling automation, deep analytics, compliance and continuous innovation rather than another silo.

Consider a gas and power desk on a volatile morning. A trader books a physical gas deal at a hub and a financial hedge against it. In Gravitas both are captured once, and within seconds the position, the mark-to-market and the desk's VaR update together, because the same event flows through valuation and limit checks automatically.

As the trader sizes the next trade, a pre-deal check shows the incremental VaR and the remaining headroom against the book's limit, so the decision is made with the risk already visible rather than discovered at end-of-day. Meanwhile an anomaly flag quietly highlights a curve point that moved far more than its neighbours, prompting the market-data team to validate the feed before it distorts anyone's P&L.

By late afternoon the scheduling team nominates the physical volume to the grid operator from the same record the trader booked, settlements sees the expected cashflow build with no re-keying, and the CRO's dashboard shows a clean, reconciled exposure across the whole desk. Nothing was assembled by hand overnight, because the platform kept one version of the truth all day.

The point of the day is not any single feature but the absence of friction between them. Because trade, risk, scheduling and settlement all draw on one governed record, the desk spends its energy on trading decisions rather than on assembling and reconciling the data that describes them, and the numbers everyone relies on are the same numbers all day long.

Gravitas is delivered with Durga Analytics' consulting, implementation and managed-service capability, not handed over as a licence at the door. The engagement is structured so that value is proven early and risk is controlled, with clear outputs at each phase and trading, risk, operations and technology stakeholders involved throughout.

A typical journey starts with a focused discovery and blueprint, moves into a build-and-validate phase where modules are configured, integrated and reconciled against your existing reports, and then settles into a run phase with SLAs where performance and controls are tuned and the more advanced AI, edge and tokenisation capabilities are switched on where they add value.

Gravitas is offered on flexible subscription models, with tiers aligned to the number of commodities, entities, users and environments in scope. Implementation and managed services are structured as separate packages, so you can choose between self-managed, co-managed or fully-managed options rather than being forced into one shape.

Most clients start with a focused desk or region to prove value quickly, then scale Gravitas across their global trading footprint on an agreed roadmap. Proof-of-concept and pilot arrangements are available for qualified teams, and multi-year engagements can include volume terms. Pricing is agreed during discovery against your actual scope rather than a per-seat list price alone.

The simplest way to begin is a short discovery conversation about your current ETRM landscape, the commodities in scope and the challenges that hurt most today. From that we can shape a demonstration against your own use cases and propose a phased rollout that starts where the value is clearest, usually a single desk or region.

From there, a focused first module or desk proves the platform against your existing reports before scope widens. Because Gravitas is modular and API-first, that first step is measured in weeks rather than years, and each subsequent module builds on the same foundation, so momentum compounds rather than restarting with every phase.

Throughout, Durga Analytics' delivery and managed-service teams stay alongside your trading, risk, operations and technology stakeholders, so the platform is landed in a live environment by people who have done it before rather than handed over as software to implement alone.