Modernizing an operational voice platform meant changing its legacy call-processing stack while preserving the business rules embedded in it. WaveAccess used AI-assisted analysis and mandatory engineering validation to reconstruct the platform’s actual behavior before replacing the voice core built on AWS Lex and Amazon Connect with Telnyx and OpenAI Realtime. This validate-first approach preserved critical logic, excluded obsolete paths, and reduced migration risk, while the new architecture simplified maintenance, removed per-firm bot builds, and strengthened security controls.
How can you accelerate the preparation of a locally installed .NET application for migration to an intranet web system without losing business logic, access rules, or the familiar interface structure? WaveAccess used AI to extract rules from the source code, validate them with the client, and build a web proof of concept. In the pilot, the requirements handoff to development was reduced from several weeks to several hours.
How do you move a business-critical application when the documentation is outdated and key logic depends on scarce platform expertise? WaveAccess used AI-assisted discovery to recover the application's business logic, data model, and user workflows, and then applied engineering validation to create a reliable foundation for migration to a modern platform.
WaveAccess automated two recurring sales and presales workflows using n8n, AI, and Microsoft Teams: preparing meeting requests for approval and prompting owners to update presales records. The automations reduced manual clarification and follow-up, improved handoff quality and data accuracy, and saved an estimated 8+ hours per week.
Most legacy modernization goes sideways early, before anyone writes new code: in discovery, where teams commit to a path without a reliable picture of how the current system works. You lock in an architecture, start building, and hit behavior the docs never captured. WaveAccess uses AI-assisted legacy discovery to reconstruct how a system actually runs, from the implementation itself, in days instead of weeks.
We helped a U.S.-based real estate agency with no prior tech experience turn a business idea into a fully functioning mobile-first platform for finding trusted local specialists. Here’s how the concept took shape, what are the key features behind the platform, how the technology works, and why the solution is well-positioned for future growth.
Discover how an international business automation company enhanced the performance and scalability of its automotive data analytics platform by migrating from a local database to secure cloud environment. This ETL project streamlined data operations and laid the foundation for long-term growth.
When Lions & Tigers, a U.S. professional staffing and workforce solutions company, needed to stabilize and scale its Dynamics 365 system, a lack of in-house IT expertise had left their self-managed setup falling short. WaveAccess was engaged not just to implement fixes, but to build a robust, scalable operational framework that solved immediate challenges while laying the groundwork for future growth.
The promise of GenAI is undeniable: unprecedented productivity gains, automated creativity, and a significant competitive edge. Yet, for many organizations, the initial excitement gives way to a harsh reality. Inefficient, biased, and costly projects are often the direct result of rushing into GenAI without a clear, business-driven strategy.
WaveAccess has entered a strategic partnership with Thebes Group, a UK-based IT consultancy and managed services provider. This collaboration brings together complementary strengths in infrastructure consulting, cloud optimization, and AI-powered legacy modernization.
WaveAccess has become an integration partner of Keboola, a cloud-based data management platform that helps organizations automate and scale their data operations. Together, we will enable faster, smarter and more efficient data implementation across industries.
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