For energy retailers, AI is an opportunity to protect margin, but only if the output can be trusted. There is a cost to not adopting AI: data stays trapped in systems, implementation takes longer than it should, and teams lose time shifting information around the business. As a result, new products can take 13-18 months to reach billing at scale, slowing innovation and leaving retailers exposed to competitors who move faster.

"Energy retailers already trust Gorilla with the calculations behind their margin. Every number follows a set of rules, is auditable, and retailers still decide what the logic should be. AI has to meet that same bar: take the cumbersome work away, leave the judgement. Gorilla already holds the structured commercial data that makes AI outputs right, not just fast, and that's what drives real adoption. Gorilla's AI can help retailers bring better propositions to their customers, faster, and without losing the flexibility that makes their pricing their own, or the integrity of the data behind it." - Ruben Van den Bossche, CEO, Gorilla

Every AI capability is grounded in the same structured data and calculation engine, following the clear logic behind every price, cost, forecast and margin number, and runs on predefined prompts. That's what makes the output trustworthy, teams can still inspect the calculation as they build confidence in it, which cuts down on the repeated manual checks that quietly erode the time saved.

The first wave of capabilities will allow retailers to:

• Explain margin movements, for every contract. Only a fraction of contracts in a B2B portfolio get reviewed due to time constraints. Gorilla's AI augments the analyst so decisions can be made for every contract, reducing avoidable margin leakage.
• Configure pricing logic, at speed. New propositions need this step before they can be sold. Gorilla's AI cuts that build time, without collapsing into generic, pre-built logic and losing the competitive edge.
• Understand the why behind a price, immediately. Adhoc queries, and month-end reasoning get figured out by hand. Gorilla's AI can share an explanation instantly, freeing pricing managers for higher-value work.

These capabilities are available in Gorilla itself, and via MCP, which connects Gorilla directly to tools like Claude and Copilot, reducing the learning curve for new users and accelerating time-to-value further.

"Most AI adoption stalls because nobody knows what to ask for. All our AI experiences in-app and via MCP runs on that same structured data, while predefined prompts mean nobody's wasting time working out how to use it in the first place. This ensures our customers will get even more value out of the platform, and faster."
- Joris Van Genechten, VP Product & Engineering, Gorilla 

Now, energy retailers using Gorilla will spend less time pulling and re-explaining information across the business, more time catching underperforming contracts before they hit the P&L, and getting new propositions to market faster, without giving up the unique customisation that makes a retailer differentiated and competitive in the first place.