The Story of Reinvention Worx
Discover the stories, innovations, and people powering the future of events at RX.
One Agentic Research Engine, Endless Applications
Agentic Deep ResearchThe real breakthrough wasn't just automating one assessment, it was building a modular agentic research engine powerful enough to be repurposed across any client, industry, or evaluation type. At its core, the tool deploys specialized AI agents that autonomously conduct deep research, synthesize public and proprietary signals, apply scoring frameworks, and generate insight-rich outputs in minutes, replacing days of slow, bias-prone manual work. Its modular agentic design means it adapts seamlessly across use cases, from AI maturity assessments and strategy discovery to lead screening, without rebuilding from scratch. Already successfully deployed across multiple clients, the engine proves that the most powerful AI investments are the ones built to scale beyond their original brief.
Evolving Software Delivery with Human-Agent Collaboration
AI SDLC ReinventionEnterprise software delivery is undergoing a structural shift and the real differentiation is no longer the AI model you choose, but how you orchestrate it. We proved this with a global Software & Platforms client running a mission-critical Payroll application on a 1.5M+ line legacy codebase. Our spec-driven, multi-agent framework evolves the traditional team setup into a true human-agent collaboration model, enabling coding agents to operate effectively across the full SDLC from scope and design through build and test, even in complex brownfield environments. The results were measured against real Jira backlog items: up to 31% effort reduction in feature development and 53% in test automation, with productivity gains across the entire delivery workflow, not just isolated tasks. Crucially, the model keeps humans in control, agents handle the mechanical, humans retain the decisions, establishing a clear, governed blueprint for AI adoption at enterprise scale.
From SEO to GEO: Winning Visibility in the Age of AI Search
AI-First DiscoverabilityAs LLMs become the new search interface, the rules of discoverability have fundamentally changed and brands that don't adapt risk becoming invisible. We built a robust Generative Engine Optimisation (GEO) operating model that evolves traditional SEO into an AI-first capability, using large-scale LLM performance testing, ranking-factor frameworks, and cross-functional optimisation to boost client visibility, authority, and sentiment signals where it matters most. Proven across telco, retail, and travel, the model has delivered measurable uplifts in citations, discoverability, engagement, and conversions. This is the new frontier of brand presence, not just ranking on Google, but being cited by AI.
One Agentic Research Engine, Endless Applications
Agentic Deep ResearchThe real breakthrough wasn't just automating one assessment, it was building a modular agentic research engine powerful enough to be repurposed across any client, industry, or evaluation type. At its core, the tool deploys specialized AI agents that autonomously conduct deep research, synthesize public and proprietary signals, apply scoring frameworks, and generate insight-rich outputs in minutes, replacing days of slow, bias-prone manual work. Its modular agentic design means it adapts seamlessly across use cases, from AI maturity assessments and strategy discovery to lead screening, without rebuilding from scratch. Already successfully deployed across multiple clients, the engine proves that the most powerful AI investments are the ones built to scale beyond their original brief.
Evolving Software Delivery with Human-Agent Collaboration
AI SDLC ReinventionEnterprise software delivery is undergoing a structural shift and the real differentiation is no longer the AI model you choose, but how you orchestrate it. We proved this with a global Software & Platforms client running a mission-critical Payroll application on a 1.5M+ line legacy codebase. Our spec-driven, multi-agent framework evolves the traditional team setup into a true human-agent collaboration model, enabling coding agents to operate effectively across the full SDLC from scope and design through build and test, even in complex brownfield environments. The results were measured against real Jira backlog items: up to 31% effort reduction in feature development and 53% in test automation, with productivity gains across the entire delivery workflow, not just isolated tasks. Crucially, the model keeps humans in control, agents handle the mechanical, humans retain the decisions, establishing a clear, governed blueprint for AI adoption at enterprise scale.
From SEO to GEO: Winning Visibility in the Age of AI Search
AI-First DiscoverabilityAs LLMs become the new search interface, the rules of discoverability have fundamentally changed and brands that don't adapt risk becoming invisible. We built a robust Generative Engine Optimisation (GEO) operating model that evolves traditional SEO into an AI-first capability, using large-scale LLM performance testing, ranking-factor frameworks, and cross-functional optimisation to boost client visibility, authority, and sentiment signals where it matters most. Proven across telco, retail, and travel, the model has delivered measurable uplifts in citations, discoverability, engagement, and conversions. This is the new frontier of brand presence, not just ranking on Google, but being cited by AI.
One Agentic Research Engine, Endless Applications
Agentic Deep ResearchThe real breakthrough wasn't just automating one assessment, it was building a modular agentic research engine powerful enough to be repurposed across any client, industry, or evaluation type. At its core, the tool deploys specialized AI agents that autonomously conduct deep research, synthesize public and proprietary signals, apply scoring frameworks, and generate insight-rich outputs in minutes, replacing days of slow, bias-prone manual work. Its modular agentic design means it adapts seamlessly across use cases, from AI maturity assessments and strategy discovery to lead screening, without rebuilding from scratch. Already successfully deployed across multiple clients, the engine proves that the most powerful AI investments are the ones built to scale beyond their original brief.
Evolving Software Delivery with Human-Agent Collaboration
AI SDLC ReinventionEnterprise software delivery is undergoing a structural shift and the real differentiation is no longer the AI model you choose, but how you orchestrate it. We proved this with a global Software & Platforms client running a mission-critical Payroll application on a 1.5M+ line legacy codebase. Our spec-driven, multi-agent framework evolves the traditional team setup into a true human-agent collaboration model, enabling coding agents to operate effectively across the full SDLC from scope and design through build and test, even in complex brownfield environments. The results were measured against real Jira backlog items: up to 31% effort reduction in feature development and 53% in test automation, with productivity gains across the entire delivery workflow, not just isolated tasks. Crucially, the model keeps humans in control, agents handle the mechanical, humans retain the decisions, establishing a clear, governed blueprint for AI adoption at enterprise scale.
From SEO to GEO: Winning Visibility in the Age of AI Search
AI-First DiscoverabilityAs LLMs become the new search interface, the rules of discoverability have fundamentally changed and brands that don't adapt risk becoming invisible. We built a robust Generative Engine Optimisation (GEO) operating model that evolves traditional SEO into an AI-first capability, using large-scale LLM performance testing, ranking-factor frameworks, and cross-functional optimisation to boost client visibility, authority, and sentiment signals where it matters most. Proven across telco, retail, and travel, the model has delivered measurable uplifts in citations, discoverability, engagement, and conversions. This is the new frontier of brand presence, not just ranking on Google, but being cited by AI.