Lazyleaf Product

BidClever AI

A full-stack AI procurement platform with ~2 million tenders processed in production.

Designed, built, and operated by the same engineering team that delivers client engagements.

BidClever AI is a procurement intelligence platform designed, built, and operated by the Lazyleaf engineering team. The platform's database holds approximately 2 million tender records sourced from government procurement portals across the United States, European Union, United Kingdom, and Canada.

Every tender is processed, documented, and vectorised for semantic matching, with the supporting infrastructure to run scoring, classification, and interpretation operations continuously and at scale.

This is not a client project. It is Lazyleaf's own product, built by the same team that delivers client engagements.

bidclever.ai

~2M+

Tenders ingested, documented, and vectorised

10x

Increase in relevant opportunity discovery

80%

Reduction in research time vs. manual

Services delivered

AI/MLData EngineeringFull-Stack DevelopmentCloud ArchitectureDevOpsBrand IdentityUX/UIProduct Design

What we built

01

AI & Data Engineering

What we built

A semantic scoring engine that ingests tender documents from four procurement markets, vectorises every entry, and scores each opportunity against client profiles using weighted matching criteria. An AI assistant that interprets full tender documents and answers compliance questions directly from the source material.

02

Software Engineering

What we built

A full SaaS application: React/Next.js front-end, Node.js API, PostgreSQL and vector database storage. Tender scoring interface, AI bid writing assistant, pipeline management, and business intelligence module.

03

Cloud & Infrastructure

What we built

Complete AWS environment including data ingestion pipelines, AI compute infrastructure, CI/CD deployment, monitoring, and security. Designed and managed by the same engineers who built the application.

BidClever demonstrates how we work. If your organisation needs the same capabilities applied to a different problem, we should talk.

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