Fast Track AI can now communicate and work directly with other AI agents across an iGaming organization after Fast Track introduced agent-to-agent support for the tool.
With the update, Fast Track’s intelligence and data science capabilities can reach operator workflows that sit outside the Fast Track interface.
Under the new setup, agents in other parts of an organization can interact directly with Fast Track AI. They can ask it for context, reason about player activity, and support better-informed decisions in their own workflows.
According to Fast Track, an agent from another area of the business could request relevant player context or intelligence from Fast Track AI without direct knowledge of Fast Track’s data structures, APIs, or internal tools.
Fast Track AI can then interpret that request, apply its domain understanding, and return the appropriate context or action within the controls the operator has established. In this way, specialist agents stay focused on their own domains while they draw on Fast Track’s data science and real-time context.
Tools versus know-how
According to the company, its approach goes further than the exposure of a set of APIs or MCP tools. An MCP implementation can make tools available to another agent, yet the consuming agent must still understand when to use those tools, how to combine them, and how the underlying platform operates.
Fast Track instead keeps that expertise within Fast Track AI. The agent understands the Fast Track ecosystem, the way its capabilities interact, and the operational context in which they are used. It can also operate within the governance, workflows and controls that each operator sets. Other agents, in turn, can work with a specialized Fast Track agent and do not need to learn how to operate the underlying platform.
“We believe organisations are moving towards a world where people and agents work together. For that to scale, a single agent cannot be expected to understand the inner workings of every system it interacts with,” said Simon Lidzén, co-founder and CEO of Fast Track.
“Fast Track AI already understands Fast Track, the player context within it, how its capabilities work together and the workflows and governance established by the operator. Agent-to-agent support means that intelligence can now participate directly in a much wider agentic organization,” said Lidzén.
“We want Fast Track AI to work alongside the other agents an operator adopts, helping them make better-informed decisions wherever those decisions are being made,” he added.
An intelligence layer for operators
Fast Track already operates as a mission-critical platform for hundreds of users in CRM, player engagement, gamification, real-time player intelligence and decision-making. Its AI and data science capabilities play a central role in the way operators interpret player behavior and model value.
The company has also continued to grow beyond CRM execution. Its platform brings together real-time player data, engagement history, gamification, gameplay risk, value modeling and AI-driven decision-making. Fast Track Rewards, Greco and True Value all form part of a wider intelligence layer, which helps operators see what is happening and decide where to act.
Agents that work past product lines
Fast Track expects the next phase of enterprise AI to center on ecosystems of specialized agents that work together across systems and teams.
“The opportunity becomes much bigger when agents stop being confined to individual products. An agent should be exceptionally good at understanding its own domain, but it should also be able to collaborate with the rest of the organization,” Lidzén continued.
“As Fast Track continues to expand its capabilities in AI, data science and modelling, we want that intelligence to become increasingly useful across the operator, not only inside one interface or one team. Agent-to-agent support is an important step in making that possible,” he said.
The company said the release forms part of its continued development of an AI-native platform.