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Building a product on a large language model is not hard. Building one that performs reliably in production, integrates cleanly with your existing systems, handles edge cases, and scales with your business is a different challenge entirely. We have done it across fintech, healthcare, e-commerce, and govtech. We know what it takes and we build it properly from the start.
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A structured build process designed around getting a production-ready LLM product into your hands, integrated with your existing systems, and performing reliably from day one.
We get deep into your use case, your data environment, your existing systems, and the specific outcomes the product needs to deliver. We define success criteria upfront, map every integration dependency, and agree the full scope before any code is written. This ensures the build that follows is exactly what your business needs, not a closest approximation of it.
We select the right model for your use case from across the available landscape including OpenAI, Anthropic, Google, and open-source alternatives. We design the architecture around your performance, cost, latency, and compliance requirements, including decisions around RAG implementation, vector database selection, fine-tuning need, and prompt engineering strategy.
We build the data pipelines that feed your LLM product with the right information at the right time. This includes ingestion, chunking, embedding, retrieval, and preprocessing where relevant. We also implement evaluation datasets and testing frameworks early so the model's performance can be measured and improved throughout the build rather than assessed for the first time at launch.
We build the full product on top of the LLM layer, integrating it with your existing systems, APIs, and data sources. Every integration is tested against your real data environment and real edge cases. We build for the failure modes that only reveal themselves in production and handle them before your users encounter them.
We run comprehensive testing across model performance, integration reliability, security, compliance, and load before anything goes live. Deployment is handled by the same senior engineers who built the system. Monitoring and observability are set up from day one so your team has full visibility into how the product is performing in production from the moment it launches.
Most LLM projects look promising in a prototype and fall apart in production. We build for production from the first line of code, which is why our LLM products ship and stay shipped.
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We have shipped LLM products in fintech, healthcare, e-commerce, and govtech. We know which architectures hold up under real load, which prompt strategies fail at scale, and which integration patterns cause problems in production. That experience goes into every build from the first sprint.
We define what a successful LLM product looks like for your business before we write a line of code. Model performance benchmarks, integration requirements, latency targets, and business KPIs are all agreed upfront. We measure ourselves against those standards throughout the build, not just at the end.
We work across OpenAI, Anthropic, Google, Mistral, and open-source models. We select the right one for your use case based entirely on performance, cost, compliance, and capability fit. We have no preferred provider and no commercial arrangement that influences that decision.
Every LLM product we build is handled by senior engineers from discovery to deployment. No juniors introduced partway through, no handoffs to a cheaper bench after scoping. The same people who designed the architecture are the ones who ship it to production.
We work across high-impact industries, combining deep domain knowledge with cutting-edge design and AI.
Document processing, workflow automation, and data systems built for the compliance requirements and complexity of government environments.
From credit risk and fraud detection to payment infrastructure and regulatory compliance, we build AI that performs where the consequences of failure are real.
Underwriting automation, claims processing, fraud detection, and risk modelling built for heavily regulated insurance environments with real accountability.
HIPAA-compliant AI systems, clinical decision support tools, and patient-facing products built with the care and rigour that healthcare environments demand.
Real-time decision systems, route optimisation, demand forecasting, and operational AI that keeps supply chains running efficiently at scale.
Personalisation engines, recommendation systems, and operational automation that drive measurable revenue lift and keep customers coming back.
Property valuation models, document processing, market analysis tools, and AI-powered platforms that bring speed and intelligence to property decisions.
Expert thinking on AI, industry trends, and the decisions that shape how businesses grow.
We’ve heard it all. Here’s everything you need to know before working with us.
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