What the client needed: An AI-powered analytics and automation layer for financial data has surfacing insights, automating reporting & detecting anomalies that manual review was missing.
What we built: NLP pipelines trained on financial document corpora; predictive analytics models for pattern detection; automated insight generation engine; anomaly alerting with configurable thresholds.
What the client needed: A smarter vendor discovery experience is moving beyond keyword search to semantic matching that understands procurement intent and vendor capability.
What we built: Custom embedding models trained on procurement taxonomy and vendor profile data; semantic similarity matching at query time; spend analytics layer on top of transactional data.
What the client needed: An AI copilot for procurement leaders the one that could generate RFP responses, analyse vendor contracts, benchmark pricing against market data & surface procurement risks.
What we built: Fine-tuned LLMs on proprietary procurement datasets; contract analysis pipeline using NLP extraction and clause-level classification; pricing benchmarking model; risk signal detection layer.
What the client needed: A marketplace that matches projects to the right freelance experts semantically just not by keyword, but by true capability and requirement fit.
What we built: Custom embedding models trained on expert profile data and project requirement language; semantic matching engine; AI-assisted project brief writing feature; automated proposal relevance scoring.
Tell us what you need. We'll tell you honestly what AI can and cannot do for it — then deliver if it stacks up.
Discuss a Custom AI Build