Lender Price is putting AI agents to work on some of the behind-the-scenes processes that keep mortgage pricing engines current, including changes to rates, loan-level price adjustments, and product eligibility.
The technology company on Wednesday introduced AI agent capabilities within POD, its AI Pricing Optimization Dashboard, designed to automate repeatable work performed by its pricing teams when investors issue changes to rates, LLPAs, programs, eligibility requirements, and pricing specials.
Rather than operating autonomously from start to finish, the agents work within defined guardrails and approval workflows. They can interpret incoming change information, prepare and validate updates, identify exceptions, and route changes requiring judgment to Lender Price pricing professionals.
“In mortgage pricing, accuracy is not a feature — it is the foundation,” said Dawar Alimi, CEO and co-founder of Lender Price. “POD is not about replacing the people who understand mortgage products, capital markets, and our clients' businesses. It is about giving them AI agents that can take on the painstaking, repeatable work so our experts can focus on controls, exceptions, and the decisions that deserve human expertise.”
The latest rollout builds on earlier phases of POD that used AI to identify potential pricing discrepancies and assist with implementation work, including organizing lender data, identifying gaps and onboarding products, programs, eligibility rules, and investor-specific pricing.
The new agents take that a step further by applying AI to the ongoing workflows used to maintain the pricing engine.
For LOs, the changes largely happen behind the pricing screen. The aim is to make the investor and pricing updates feeding that system faster and more consistent while reducing opportunities for manual configuration errors.
Lender Price is targeting up to a 90% reduction in manual touchpoints for eligible, repeatable rate-sheet and pricing-update workflows and up to 75% faster preparation and validation of routine LLPA, pricing-special, and program changes.
The company is also targeting at least 99.9% traceability for POD-processed changes through source links, validation records, approvals, and audit logs.
Those figures are forward-looking operating targets, not measured customer performance results. Lender Price said it plans to validate and publish results as POD deployments mature.
The launch continues an AI strategy Lender Price has been building throughout the year.
In May, Lender Price launched its Model Context Protocol server, which allows lenders to connect AI agents and large language models directly to live pricing intelligence, including rates, eligibility rules, overlays, and investor guidelines.
While that initiative focused largely on allowing AI-powered tools to access and interact with pricing information, POD applies AI to the operational work involved in keeping that information current.
“The future of POD is a more accurate, more resilient pricing operation,” Alimi said. “Our people remain essential. AI agents make their expertise more powerful by helping ensure that every update — from an LLPA change to a pricing special or eligibility rule — is handled with discipline, visibility, and speed.”
