Tabi Connect, a leading AI-powered rate management and freight quoting platform, announced the launch of its AI Dynamic Business Rules Engine at Manifest 2026. The new engine enables freight brokers to build, manage, and adjust complex pricing logic using plain English, without code, allowing teams to respond instantly to market changes while maintaining full auditability and control.
For decades, freight quoting relied on manual workflows and tribal knowledge. Pricing teams copied and entered data across shipper portals, emails, spreadsheets, and TMS systems, applying experience-based assumptions to calculate rates. These processes were slow, inconsistent, and difficult to scale.
Tabi Connect replaces this approach with an AI-driven decision layer that turns pricing strategy into automated business logic.
“Freight brokers operate in highly dynamic markets, yet most pricing systems still depend on static rules and heavy manual input,” said Ricardo Gonzalez, CEO and Co-Founder of Tabi Connect. “We’ve already helped one $4B+ brokerage generate over $100 million in new revenue with a small team managing pricing logic. Now, with AI-powered Dynamic Business Rules, that same impact becomes simpler and more powerful. Brokers can update strategy in real time using plain English and scale quoting without adding headcount.”
Compared with rate engines built around fixed logic or IT-led configuration, Tabi Connect’s Dynamic Business Rules Engine allows users to stack multiple parameters, including lane, customer, equipment type, accessorials, or market conditions, into flexible, non-destructive rules. Changes can be implemented across workflows without overwriting existing logic, reducing risk while increasing speed and consistency.
The Dynamic Business Rules engine is powered by Tabi Connect’s embedded AI Assistant, which translates plain-English instructions into structured business logic, accelerating onboarding and reducing configuration errors. Built-in versioning, permissions, and rollback capabilities ensure every change is traceable, reversible, and governed, which is critical for teams operating at scale.
