What We Do — and What We Do Not Claim
In 2021, TGSlive formally integrated AI and advanced analytics tooling into our own delivery model. Not as a product launch — as an internal capability upgrade. We used it to improve demand forecasting accuracy on client engagements, automate document-heavy workflows, and build operational dashboards that previously required weeks of analyst time.
By 2023, clients began asking us to deploy those same capabilities within their own operations. Today we have a dedicated team of 9 AI engineers and data scientists who build, deploy, and maintain AI solutions in production enterprise environments — with a deliberate focus on integration into existing ERP and data systems, not standalone tools that create new silos.
We do not claim AI is a transformation strategy. It is a capability layer. The organisations that get value from it are the ones that already have clean data, clear ownership, and a process to change. We help build those foundations — and then we add the AI.
What We Deploy
- ML-Based Demand Forecasting — Time-series and ensemble models that improve demand accuracy by 25–40% over statistical baselines. Deployed into SAP, Oracle, and Dynamics ERP systems — not as a standalone forecasting tool.
- Intelligent Document Processing — LLM-powered extraction, classification, and validation of contracts, invoices, purchase orders, bills of lading, and compliance documents. Typical reduction of 70–85% in manual processing time.
- Operational Anomaly Detection — Machine learning models that identify process deviations, quality escapes, and cost overruns in real time — surfaced in existing BI dashboards, not new portals.
- Workflow Automation — End-to-end automation of approval chains, reporting workflows, and exception-handling processes. Reduces manual intervention and processing backlogs in finance, procurement, and operations functions.
- Custom AI Solutions — For clients with a specific, well-scoped problem. We scope, build, test, deploy, and maintain. Internal knowledge assistants, automated reporting engines, pricing optimisation tools, and client-facing AI features.
- AI Readiness Assessment — A structured 3-week assessment of your data quality, infrastructure, and organisational readiness for AI deployment. Honest about what is and is not feasible in your current environment.