Tavant debuts agentic AI platform for software engineering, automation

Tavant launched the Tavant Platform, a three-layer enterprise solution that combines agentic engineering tools, an optional runtime and domain-specific automation components. Built around the company’s AIgnite framework and supported by its AWS Generative AI Services Competency, the platform targets use cases in mortgage lending and other industries. AI Summary

Tavant has introduced a new enterprise platform that uses agentic AI to accelerate software development, data modernization and automation. The California-based technology firm positions the Tavant Platform as an alternative to proprietary AI stacks and high recurring platform fees, the company announced June 23.

The Tavant Platform brings together three core layers: a suite of agentic engineering tools built on top of coding agents from major artificial intelligence labs; an optional cloud-native runtime foundation; and a set of domain-specific automation components, models, agents and specifications, according to a company press release.

The platform incorporates Tavant ’s existing AIgnite agentic engineering tools and can be deployed either on Tavant’s own runtime or on a customer’s preferred technology stack. Tavant said this approach is designed to keep enterprise architectures portable and reduce vendor lock-in, an ongoing concern as more organizations embed generative AI into core business processes.

Rethinking pushed by LLM disruption

Tavant is initially targeting use cases in mortgage lending and the equipment aftermarket with enterprise automation products that now run on the Tavant Platform. For housing and mortgage firms, the company said the platform is aimed at modernizing legacy loan origination and servicing systems; automating workflows such as underwriting, risk and fraud checks ; and building custom applications when licensed point solutions are too costly or inflexible.

“The Large Language Model disruption is forcing enterprise leaders to rethink everything from workforce productivity to legacy system modernization, the level of enterprise automation, the platforms they rely on, and the governance and security needed to use AI safely,” CEO Sarvesh Mahesh said in the release.

Mahesh said general-purpose coding agents need domain-specific specifications, skills and architectural patterns to deliver productivity gains inside large organizations, which the platform is intended to provide.

Tavant framed the launch within a broader shift from AI pilots to production deployments. Chief technology officer Manish Arya said the main challenge for enterprises is “execution at scale with the right architecture, governance, and operational rigor.”

AI-enabled mortgage workflows

Tavant recently achieved the Amazon Web Services ‘ (AWS) Generative AI Services Competency, which the company said supports its ability to help clients move from early-stage concepts to production AI systems.

Agentic engineering refers to using AI “coding agents” that consume detailed specifications to generate software, data pipelines, models and workflows with less manual coding. Tavant said its platform applies this approach to three main areas: modernizing legacy applications and data platforms; automating business processes with AI; and building custom applications where off-the-shelf products are not economical.

For financial services firms, including mortgage lenders , the company said the platform is intended to support AI-enabled workflows in risk, fraud detection, underwriting, customer service and back-office operations. The platform is built using cloud-native and open-source components, and it offers customers the option to obtain runtime and tool source code if they later choose to operate independently of Tavant’s managed stack.

Tavant calls the platform a “true alternative” to existing enterprise AI automation platforms by combining a pre-integrated agentic engineering toolchain with optional runtime and services support.

For lenders and servicers weighing AI investments, the company is emphasizing lower development and maintenance costs, reduced dependency on proprietary platforms and faster deployment of automation around legacy mortgage technology.

This article was generated using HousingWire Automation and reviewed by a HousingWire editor before publication.