SelectHub has announced the launch of DataGrout, its specialized AI research lab introducing an LLM inference optimization platform and AI governance solution for enterprises. DataGrout’s mission is to drive token reduction for agentic workflows, chatbots and AI tools, while equipping IT and FinOps leadership with a policy-driven, auditable LLM payload and cost monitoring system to track company-wide AI utilization.
As enterprise users increase LLM usage through context-intensive chat sessions and coding tools such as Claude Code, Cursor and Replit, uncontrolled token waste and hidden API expenses are putting significant strain on corporate budgets. This is especially impactful as organizations also begin expanding agentic workflow deployments across diverse use cases such as customer service and sales outreach.
DataGrout addresses this challenge through a unified connection layer that enables agents to securely access all enterprise applications with built-in dynamic context pruning, alongside a symbolic inference layer that reduces calls to the underlying LLM. Early tests have shown promising results with token reduction averaging 60% for data-intensive tasks involving ERP and CRM integration, without compromising workload accuracy.
“Companies are flying blind into the AI era,” said Venkat Devraj, CEO at SelectHub. “Through DataGrout, IT and Finance teams gain precise token tracking and visibility into LLM consumption patterns and payloads, enabling leadership to clearly measure the value delivered by AI investments while systematically eliminating waste on a per LLM-call basis. Deterministic workloads are kept off the LLM entirely without users and developers having to manually segregate and route workloads. The net positive impact on the P&L is instantaneous.”
The critical market need for tools that help IT and FinOps / AI Tokenomics teams audit and eliminate token waste is being echoed across enterprise leadership.
Deepak Dodani, Chief Information Officer at global transportation management and freight audit firm AFS Logistics, noted: “The twin challenge for companies deploying AI is token economics and governance. Right now, most companies cannot accurately assess the extent to which their LLM resources are driving business value versus being drained by unnecessary or unauthorized side-projects. DataGrout’s premise in terms of reducing token waste while enabling visibility into LLM usage, is very timely.”
Bharath Prabhakaran, Chief Digital Officer at University of Cincinnati, also emphasized the need for enterprise LLM usage tracking and agent governance: “Rampant LLM token usage has many CIOs and CFOs worried. AI line items can quickly become one of their fastest-growing operational expenses. Without visibility into LLM usage and token consumption metrics that show which teams and use cases consume the most tokens, forecasting ROI is nearly impossible. DataGrout endeavors to reduce token usage while increasing the transparency needed to reduce waste and prevent abuse.”
DataGrout acts as a MCP gateway and control plane with agents connecting via its Conduit SDK or via MCP or JSON-RPC. DataGrout allows any third-party MCP server to be accessed through its platform, while also offering its own MCP servers for popular SaaS applications such as Salesforce, HubSpot, Oracle ERP, SAP, ServiceNow, Snowflake and QuickBooks. DataGrout can be connected to LLMs directly with companies bringing their own key, or via popular AI gateways such as Amazon Bedrock and Kong.