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.
Multi-agent systems often show managerial problems: agents fail to share information, follow roles mechanically, or drift into unproductive chatting. Today let’s see why good engineering is more important than improvement of prompts.
By shifting from isolated AI pilots to a centralized enterprise framework, businesses can finally automate complex workflows and accelerate decision-making without compromising on governance or LLM independence. Here’s how we solve these scaling challenges with our enterprise-ready solution.
When every department builds its own AI agent with its own data, logic, and tools, organizations can find themselves with a "zoo" of disconnected systems. Instead of scaling, these silos cause the company to slow down. Paul Chayka, Integration and AI Solutions Expert, breaks down how to innovate responsibly by selecting the right initial use cases, and shifting from simple task automation to a coordinated multi-agent ecosystem.
For a Forbes Global 2000 client, we automated the process of matching adverse event descriptions from clinical reports with standardized MedDRA vocabulary — achieving over 95% automation, including terms that specialists previously failed to map manually. Faster and more accurate processing of clinical data reduces R&D costs, accelerates regulatory submissions, and ultimately supports faster delivery of new treatments.
At WaveAccess’s first AI Jam, a collaborative, role-play session built on authentic AI use cases, business leaders exchanged perspectives on what works with AI today and what still needs clarity. The conversation surfaced both practical opportunities and shared concerns around accountability and leadership.
We developed a GenAI search platform for a major pharma company, transforming a days-long, manual research process across scientific resources into a task taking a minute. The solution accelerates drug development cycles, reduces high-value labor costs, and improves patient outcomes by ensuring critical scientific insights are captured and acted upon instantly.
Vibe coding — the practice of writing code through natural language interactions with AI — has become a hot topic across the corporate tech world. But in practice, it’s meeting a wall of cultural caution, productivity paradoxes, and real-world quality challenges. Here is our look at the current state of adoption, risks, and the emerging best practices for companies bringing AI-assisted coding into their development pipelines.
A major pharmaceutical company needed to improve how its medical staff learned about new products. Their manual process for analyzing training tests was inefficient. We developed an AI system that pinpoints weaknesses in training materials, allowing for quick, precise improvements. The result was an increase in knowledge retention and a more efficient training process.
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