The AI-ready data infrastructure your. models actually need
Vector databases, scalable data pipelines, and AI-native storage architectures — built to handle the throughput, latency, and scale that production AI systems demand.
Start where you are.
Build toward the frontier.
We meet you at your current maturity level and build a clear path forward — from foundational implementation to research-grade capability.
Data Pipelines
- Ingestion pipelines for structured & unstructured data
- ETL & streaming pipelines (Kafka, Flink, Spark)
- Data lake & lakehouse architecture design
- Schema versioning & data contract management
- Real-time feature engineering for ML systems
Vector & Search Infrastructure
- Vector database deployment & optimisation (Qdrant, Weaviate, Pinecone)
- Hybrid search index architecture
- Embedding storage & versioning strategies
- Multi-tenant index partitioning
- Sub-100ms retrieval at 100M+ document scale
AI Infrastructure Platform
- Model registry & artifact management
- Training data versioning (DVC, LakeFS)
- Experiment tracking & lineage (MLflow, W&B)
- GPU cluster management & job scheduling
- Cost attribution & infrastructure observability
Shipped artifacts, not slide decks.
Every engagement ends with working software, documented systems, and a team that knows how to extend them.
Data ingestion & transformation pipeline
Production-grade pipelines handling your data sources — batch and streaming — into AI-ready formats.
Vector store deployment & tuning
Optimised vector database configuration, sharding, and scaling strategy for your data volume and query patterns.
ML platform & tooling
End-to-end ML infrastructure — experiment tracking, model registry, and artifact lineage — ready for your team to own.
Observability & cost monitoring
Infrastructure dashboards covering throughput, latency, error rates, and per-job cost attribution.
See it in production.
Real engagements from this practice area — the challenge, the build, and the outcome.
4 mo.
Brief to production
- 4 platforms shipped simultaneously — Windows, iOS, Linux & Web
- Bidirectional cloud sync with conflict resolution
- $100K+ in hiring costs saved vs. traditional recruitment
From Brief to Production AI Storage Platform — in Four Months
A complete AI-powered storage platform shipped across Windows, iOS, Linux, and Web — with bidirectional cloud sync, multi-OS clients, and enterprise RBAC — in four months flat.
Your FinTech & Accounting
AI stack
starts with one call.
Book a 30-minute strategy session. We'll map your specific opportunity in fintech & accounting ai, identify the highest-leverage starting point, and tell you exactly what an engagement looks like.