Enterprise AI Gateway & Policy Routing Engine
Large enterprise teams were copy-pasting sensitive operational and commercial data into public AI chat interfaces, presenting severe data leakage risks and violation of compliance protocols.
We engineered a unified, secure corporate AI Gateway. The engine intercepts model requests, validates them against dynamic security policies, maps user permissions, and routes queries to either local open-weight models or approved enterprise API endpoints.
Secured corporate IP and logged all queries for compliance audits. Reduced API token costs by 40% through intelligent prompt-caching and routing parameters.
Cross-Subsidiary Knowledge Federation
Operations and engineering teams wasted hours searching for specific technical manuals, well logging data, geology reports, and regulatory compliance documents across scattered network directories.
We built a private Retrieval-Augmented Generation (RAG) network. The system parses unstructured PDFs and spreadsheets, indexes them into a secure vector database, and allows teams to query the data with natural language, receiving precise answers with exact page citations.
Information retrieval cycles moved from manual directory searches to cited answers delivered in seconds, giving engineering teams immediate access to verified corporate knowledge.
Financial Intelligence & Market Monitor
Investment offices and research analysts spent valuable hours scraping stock exchanges, reading PDF financial reports, and manually updating portfolio spreadsheets.
We designed an AI-assisted financial data processing pipeline that tracks exchange filings, corporate action announcements, and dividend schedules. The engine extracts key numbers and structures them into chronological markdown dossiers.
Automated monitoring of 190+ active equities, generating real-time dashboards that cut reporting cycles by 30-70% and provide analysts with instant data visibility.
Sovereign Cloud & Local Hosting Framework
Relying on external cloud APIs was proving expensive and posed regulatory issues for national security data and local corporate information.
We structured a local cloud deployment framework designed for private hosting of open-weight models (e.g. Llama-3, DeepSeek). We mapped server requirements, optimized inference containers, and integrated them with local networks.
Handled sensitive data in a fully isolated local private cloud environment while reducing cloud processing costs by 50% compared to equivalent external APIs.
Agentic Business Operating System
Operational workflows were fragmented across separate Google Sheets, Slack channels, Drive folders, and legacy databases, causing communication delays.
We built an agentic middleware layer. When files or database entries are updated, custom event triggers run and utilize model extraction rules to summarize logs, update dashboards, and alert relevant teams via Slack.
Connected file and database events to dashboard updates, Slack notifications, and timestamped audit records, eliminating repeated handoffs across disconnected tools.
