Recent AI Systems Shipped by Otairo

SEC filings are long, inconsistent, and unstructured. Critical signals relevant to board opportunities are buried across sections and formats, making manual review slow, costly, and easy to miss.

Researchers were spending hours each day scanning filings, interpreting context, and tracking potential opportunities with limited tooling.

Otairo built an end-to-end AI system that continuously monitors SEC filings and applies contextual analysis to identify board-seat opportunities.

The client relies on a commercial POS (Point of Sale) system to run the business, but its built-in reporting was too limited for the questions the team needed to answer.

Each season, they needed to understand what sold, what did not, which customers bought which products, and how that should shape future buying decisions.

Otairo built an AI-enabled analytics and automation platform that works alongside the client's existing POS system, using synchronized sales, inventory, and customer data. Beyond custom dashboards, the platform lets the team ask business questions in plain English and get answers powered by AI-generated SQL, validated before execution, so they are not limited to a fixed set of static reports. It also includes an AI-assisted workflow for image-based product lookup and customer question answering. When a customer sends a product image over WhatsApp, the system identifies the item from indexed catalog images and answers questions like size availability without a manual POS search.

Hiring teams often work from unstructured job descriptions and resumes, making it slow and difficult to compare candidates consistently. Key qualifications are buried in freeform text and document layouts, so screening often depends on manual review and subjective interpretation.

Otairo built an AI-assisted resume evaluation application that structures both sides of the hiring process and uses that data to generate detailed candidate-job match reports.

Notary staff were manually reading uploaded government documents, receipts, and other supporting records, then retyping key information into legal templates.

This process was slow and error-prone, especially when source files were low-quality scans or phone photos and the required values included hard-to-read names, addresses, and serial numbers.

Otairo built an AI-assisted proof of concept that helps users extract text from uploaded document images, map that text into template fields, and generate a completed output document.

The system also captures how users map source content into template fields so similar documents can be pre-filled more efficiently in the future, while flagging uncertain extractions for human review.

A client wanted end-to-end visibility into how work moves through the SDLC so they could spot bottlenecks, improve predictability, and track quality. But the starting point was a high-level RFC that left too many details undefined, which made delivery estimates conservative and metric accuracy uncertain.

Otairo ran an analysis and architecture phase to turn the request into an implementation-ready reporting plan. We used AI to synthesize interviews and existing artifacts into consistent metric definitions and a warehouse-ready blueprint.

A global automotive finance modernization program needed multiple backend interfaces to connect a new platform to legacy and downstream systems.

Otairo delivered four production-grade interfaces using AI to speed spec work and keep patterns consistent. AI was used heavily to turn fragmented inputs into buildable specs and to generate consistent implementation scaffolding from interface contracts.