Trusted by Our Clients








The problems supply chain leaders face daily
Traditional demand planning struggles with volatile markets, seasonality, and sudden disruptions.
Data scattered across ERP, WMS, TMS, and supplier portals makes end-to-end monitoring difficult.
Supplier delays, transport issues, or geopolitical risks are identified too late.
Manual vendor evaluation and negotiation slow down sourcing cycles and increase costs.
Freight, inventory holding, and compliance penalties cut into margins.
AI agents operate continuously across your supply chain ecosystem:
They ingest data from ERP, supplier portals, logistics providers, and market signals.
They detect risks early—from supplier delays to transport disruptions.
They recommend actions like rerouting shipments, adjusting safety stock, or switching suppliers.
They automate repetitive tasks such as bid analysis, demand-supply balancing, and reporting.
They learn from outcomes and adapt strategies, becoming more accurate and effective over time.
Machine learning models factor seasonality, promotions, and external events to improve forecast accuracy by up to 20–30%.
AI agents recommend reorder points and safety stock adjustments to reduce both stockouts and excess inventory.
Automated monitoring of supplier performance, financial health, and compliance to flag risks proactively.
Dynamic routing and delay prediction to cut freight costs and improve on-time delivery.
Automated comparison of supplier bids, contract clause checks, and cost benchmarking.
Intelligent alerts that highlight disruptions and suggest corrective actions in real time.
By providing real-time insights and actionable recommendations.
reduction in working capital
Tied to inventory through smarter stock management.
fewer stockouts
And lost sales with demand-supply alignment.
logistics cost savings
By optimizing routes and reducing expedited shipping.
faster procurement cycles
Through automated vendor evaluation and compliance checks.
Works with SAP, Oracle, Microsoft Dynamics, and industry-specific ERPs.
Tailored to each supply chain environment, not generic automation.
Delivered predictive analytics and automation to Fortune 500 supply chains.
SOC 2, GDPR, and ISO-aligned practices.
Discover how we've helped businesses transform with intelligent AI solutions.
Built a multimodal AI agent platform for compliance teams, unifying access to archived emails, attachments, and documents across S3, databases, and internal systems. Agents handled ingestion, semantic retrieval, natural language interaction, and feedback learning, enabling context-aware search, AI-generated summaries, and faster audit readiness.
We developed a multi-agent AI system that reimagines how users assess, monitor, and improve data quality, enabling intelligent collaboration, automation, and real-time decision-making.
Multimodal GenAI-powered automated customer service platform for a large Electrical and Electronics Manufacturer, supporting NLP, image, audio, and video inputs for contextual insights and personalized information delivery.
LLM-powered healthcare knowledge assistant enabling scientists to retrieve complex clinical, chemical, and lab-related data using voice and text, reducing research time and improving accuracy in labs.
Narrative Generation Agent integrated with BI tools like Power BI, Tableau, and Qlik, transforming raw dashboard data into real-time natural language insights for faster decision-making.
GEN AI and ML-powered real-time Q&A system that analyzes user queries, recommends high-confidence responses, and continuously learns from user feedback to automate repetitive support functions.