Industries we serve
Secure, compliant platforms for banking, fintech, and wealth management where downtime is not an option.
Revenue intelligence, booking systems, and high-touch digital experiences for premium travel brands.
Adaptive learning platforms, LMS infrastructure, and AI-powered content operations for global institutions.
Smart property platforms, resident applications, and ESG reporting tools for the built environment.
ERP modernization, process automation, and data platforms that enable large organizations to operate with speed, control, and global scale.
Environmental impact tracking, ESG reporting infrastructure, and compliance platforms for responsible organizations.
Content platforms, streaming infrastructure, and monetization systems built to scale audience engagement and performance.
DATA & STORAGE
We design relational, document, key‑value, and vector storage that fits your workloads—from transactional systems to AI‑driven experiences.
PostgreSQL, MongoDB, SQL Server, DynamoDB, Redis, and vector databases each play a specific role in your data platform, and we help you put them together safely.
PostgreSQL & SQL Server for transactional and reporting workloads.
MongoDB for flexible schemas and evolving products.
Vector databases for semantic search and AI retrieval.
DynamoDB for high‑throughput, low‑latency access patterns.
Redis for caching, sessions, queues, and real‑time features.
Automated backups, restores, and DR plans built into the platform.
Advanced relational database for complex transactional and analytical workloads.
Document database for evolving schemas, content, and user‑generated data.
Specialised stores for embeddings and semantic search powering AI retrieval.
Microsoft SQL Server for line‑of‑business apps, reporting, and integrations.
AWS NoSQL database for high‑throughput, low‑latency workloads at scale.
In‑memory store for caching, sessions, queues, and real‑time features.
We align storage choices with access patterns, consistency needs, and the way AI and analytics will use your data—so you avoid over‑engineering or premature bottlenecks.
OLTP vs OLAP, read/write ratios, and multi‑tenant requirements all influence whether we choose relational, document, key‑value, or vector storage.
We plan for growth and change: schema migrations, versioned APIs, blue‑green or online migrations, and clear rollback strategies.
Backups, restore testing, security controls, and monitoring are treated as first‑class features of your data platform—not afterthoughts.
How we design, migrate, and operate the databases that sit underneath your products and AI systems.
We look at access patterns, data relationships, and future reporting needs. Often the right answer is a small combination of stores rather than a single database for everything.
Yes. We improve performance, reliability, and developer ergonomics around the databases you already use, and only introduce new technology when it clearly pays for itself.
We separate transactional and analytical concerns, design clean event or ETL pipelines, and add vector stores where AI retrieval or personalisation benefits from embeddings.
We plan and execute migrations with staged rollouts, verification, and fallbacks so your teams always know the state of the data during the change.