From invoice automation to market intelligence, our AI agents are solving complex business challenges and delivering measurable results across industries.
Automated invoice scanning, categorization, and booking allocation for a fulfillment services company
A fulfillment company manages operations for multiple clients, receiving hundreds of vendor invoices monthly in various formats (PDF, Excel, scanned documents). Each invoice line item needed to be accurately attributed to the correct client project, then summarized and forwarded for billing.
Manual processing was time-consuming, error-prone, and created bottlenecks in the accounting workflow. Misallocated costs led to billing disputes and strained client relationships.
We built an AI agent system leveraging Microsoft Azure ecosystem and advanced LLMs that automatically processes incoming invoices through a sophisticated pipeline:
Reduction in manual processing time, from 40 hours to 6 hours per month
Fewer misallocations and billing errors through consistent AI-driven categorization
Complete invoice coverage with flagging system for ambiguous cases requiring human review
Continuous accuracy gains over 6 months through reinforcement learning from CSM feedback
Real-time monitoring and analysis of supply chain disruptions and market movements
Manufacturing and supply chain teams struggle to stay ahead of market disruptions. Component shortages, mineral scarcity, transportation blockages, and geopolitical events can cripple operations, yet these signals are scattered across news sources, industry reports, and social media.
Manual monitoring is impossible at scale, and by the time disruptions are noticed, it's often too late to adjust procurement strategies or find alternative suppliers.
We developed a cloud-hosted AI radar system built with a Python backend and React frontend that continuously scans global news sources, industry publications, and specialized databases to detect and analyze market-moving events:
Average lead time before disruptions impact operations, enabling proactive responses
More sources monitored compared to manual research, uncovering risks previously invisible
Fewer surprise disruptions through comprehensive monitoring across regions and sectors
Estimated annual savings from avoided stockouts and optimized procurement timing
AI-powered CRM intelligence for authentic, tailored outreach at scale
Modern buyers are exhausted by generic mass marketing. Sales teams using CRM platforms struggle to balance scale with personalization—either they send templated messages that get ignored, or they spend hours researching each prospect individually.
First responses from prospects contain valuable signals about their needs, pain points, and readiness to buy, but these insights often get lost in high-volume workflows. The result: missed opportunities and low conversion rates.
We created an AI agent system built with Python that integrates directly with CRM platforms via APIs, using vector databases for intelligent lead matching and context retrieval to transform how sales teams identify, qualify, and engage leads:
Increase in initial response rates through highly relevant, personalized outreach
Improvement in identifying qualified leads through AI-driven analysis of signals and context
Faster initial contact with hot leads through automated research and prioritization
Of prospect signals captured and analyzed, eliminating manual oversight gaps