Ship AI that holds its place in production
We design, build, and deploy machine learning and generative-AI systems that hold up under real users and real data, not demos that stall once the pitch ends.
We start with your problem, not the technology. Sometimes the right answer is a model in production, sometimes it's simpler automation, and sometimes it's that you don't need AI at all. We'll tell you honestly which.
Custom AI development services
Every engagement starts with the problem, then the smallest approach that solves it in production. Pick a capability to see how we approach it.
Agentic AI & custom LLMs
We build agentic systems and custom LLM applications that reach well past basic chatbots, able to hold context, use your own tools, and carry out multi-step tasks on their own.
How we help
The hard part is moving from a simple LLM call to something production-grade. We engineer dependable architectures with memory, tool use, and safety layers so the system holds up under real load.
We build agentic systems and custom LLM applications that reach well past basic chatbots, able to hold context, use your own tools, and carry out multi-step tasks on their own.
How we help
The hard part is moving from a simple LLM call to something production-grade. We engineer dependable architectures with memory, tool use, and safety layers so the system holds up under real load.
We build models around your data and your goals, spanning the full path from data collection and feature engineering through training and deployment.
How we help
Teams often reach us after struggling with brittle models and code they can’t maintain. We build pipelines that adapt as data and needs shift, with clear standards and built-in observability for the long haul.
We build AI-driven forecasting for customer behaviour, demand planning, and risk detection, turning statistical models and real-time data streams into decisions you can act on.
How we help
The real challenge isn’t the model, it’s fitting it to how you operate. We design systems that plug directly into your workflows so decision-makers get timely, relevant output.
We build NLP pipelines for semantic search, sentiment analysis, and intelligent assistants, surfacing trends and opportunities hidden in your text.
How we help
We run NLP at scale by pairing transformer models, vector search, and pipelines for both streaming and historical data, integrated into your platform and compliant with your privacy standards.
We build AI that streamlines operations, from ticketing and predictive support to claims processing and fraud detection, often alongside RPA to reduce manual effort.
How we help
Good automation starts with workflows, not tech. We map what should be automated, structure the input and output, and add fallback logic so the system grows with your business.
We embed generative AI into your platform for personalized marketing, automated content, and virtual assistants, tuned to sound like your own brand.
How we help
Generative features carry real risk. We contain it with secure prompt engineering, output validation, content filters, and human-in-the-loop controls to keep results on-brand and compliant.
We build enterprise-grade data analysis, BI, and visualization platforms that put your data to work in decisions across every team.
How we help
We integrate with Power BI, Tableau, and Looker, or build custom ML-backed dashboards, designed to scale, so advanced analytics isn’t reserved for the largest teams.
We build AI that sharpens forecasting, inventory management, and route planning, combining predictive models with real-world constraints to fine-tune stock and fulfilment.
How we help
Our engineers integrate with ERP and inventory platforms such as SAP, NetSuite, and Oracle, aligning to your processes to minimize risk and maximize value.
AI we've shipped
View all case studiesWill it reach production?
We take models from prototype to production with MLOps, monitoring, and safety layers, and stay accountable for how they perform under real load.
Is our data ready?
Every engagement starts by assessing whether your data can actually support the outcome, so we don’t build a model your data can’t feed.
AI experts, AI-augmented
These are the AI coding tools our engineers use to ship faster and keep code clean, distinct from the AI systems we design and build for you.
We use these tools inside strict guardrails, every line is reviewed by a person. See how we build →
Senior AI engineers
Engineers with real, hands-on ai experience who take ownership of the work, not juniors learning on your budget.
Production-grade delivery
We take work from prototype to production, with testing, monitoring, and clean handover, not demos that stall after the pitch.
Security & compliance
Safeguards from day one. We build to and align with the standards regulated industries expect, including HIPAA, SOC 2, and ISO 27001.
Tools for AI development
Industry-standard frameworks, modern tooling, and proven internal processes, pick an area to see what we reach for and why.
We build and train models on mature, high-performance frameworks, guided by internal playbooks for architecture and training. The framework follows the problem, we don’t pick one for fashion.
We build and train models on mature, high-performance frameworks, guided by internal playbooks for architecture and training. The framework follows the problem, we don’t pick one for fashion.
For classic modelling we reach for well-tested libraries and standardized workflows for features, evaluation, and tuning. Tool choice comes down to accuracy, speed, and how interpretable the result needs to be.
We build the pipelines that turn raw, messy inputs into clean, feature-ready datasets. Scalable orchestration keeps them running reliably and wired into the systems you already have.
Before any modelling, we shape and validate the data with structured, repeatable workflows. That’s where anomalies get caught and assumptions get tested, so the model learns from something trustworthy.
We train and serve on cloud-native services with GPU support and auto-scaling, so compute expands and contracts with demand. Managed infrastructure means less ops overhead and a bill you can predict.
We work in collaborative, reproducible, version-controlled environments so experiments can be rerun and reviewed. Standard toolchains across projects keep hand-offs clean.
Our engineers use AI coding assistants for suggestions, documentation, and error-catching, shipping faster while keeping the code clean. The tools speed the work; senior review keeps it honest.
We serve models with low latency and high availability, with packaging, versioning, and rollback handled up front. Every model is deployable, monitorable, and easy to fold into your existing services.
We track drift, trigger retraining, and keep version history and audit trails across deployments. Dashboards and alerts keep models accurate, compliant, and aligned as the world shifts underneath them.
How you'd work with us on AI
Pick the level of ownership that suits you. We shape the engagement around your goals.
Staff augmentation
Add senior AI engineers to a team you already have.
Dedicated team
A committed AI team that runs like your own.
Full delivery
Hand over the build and we deliver it end to end.
AI FAQ
Have an AI idea worth testing?
Bring us the problem, we’ll tell you honestly whether AI is the right tool and how we’d build it.