Services

Deep engineering expertise across AI, machine learning, and scalable digital systems built for real-world performance.

AI & Machine Learning

Python

TensorFlow

Predictive Analytics

Data Systems

We design and deploy custom machine learning systems that automate complex workflows, uncover actionable insights, and enhance decision-making. Each model is engineered for precision, scalability, and seamless integration into real-world business environments.

Cypress

6X

Model Efficiency

70%

Reduction in Manual Work

Cypress was losing hours daily to manual review cycles in their logistics workflows. We built a predictive ML engine trained on three years of their operations data, capable of forecasting demand shifts and auto-routing decisions without human intervention. Their ops team now focuses on judgment calls, not spreadsheets.

Picture of David T.

David T.

Technical Lead, Cypress

Application Development

React

Next.js

Node.js

UI/UX Systems

We develop high-performance web applications powered by AI, combining robust backend systems with intuitive interfaces. Each application is built for speed, scalability, and seamless interaction across complex workflows and user environments.

Capmark

3X

User Engagement

2X

Conversion Rate

Capmark’s outdated loan portal had users dropping off mid-application, and support teams were overwhelmed with basic queries. We rebuilt it with an embedded AI assistant that guides clients through document submission, surfaces relevant products, and answers questions in real time, cutting drop-off at every major step.

Picture of Sarah J.

Sarah J.

Product Manager, Capmark

Cloud Services

AWS

Google Cloud

MLOps

Infrastructure

We design secure and scalable cloud infrastructures optimized for AI workloads, ensuring high availability and performance. Our systems support efficient deployment, monitoring, and scaling of machine learning models across dynamic enterprise environments.

Visualsoft

5X

Scalability

50%

Latency Reduction

Visualsoft’s on-premise AI rendering setup crashed under peak sales traffic. We migrated their workloads to a cloud-native architecture with auto-scaling GPU clusters and edge caching, handling up to 40,000 concurrent requests with zero downtime and no drop in render quality during their highest-traffic events.

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Emily R.

Director of Product, Visualsoft

Foundation Models

Hugging Face

Llama

Fine Tuning

Pretrained Systems

We customize and optimize large-scale foundation models to align with specific enterprise use cases. This approach reduces development time while maintaining high performance, adaptability, and efficiency across complex, data-intensive environments.

Infotech

5X

Faster Deployment

40%

Efficiency Gain

Infotech’s engineers struggled to navigate years of internal documentation and kept escalating repetitive queries to senior staff. We fine-tuned a foundation model on their full knowledge base and integrated it with their ticketing system. New engineers were onboarded in days, and senior staff stopped being pulled into avoidable escalations.

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Rebecca L.

VP of Engineering, Infotech

Generative Ai

OpenAI

Diffusion Models

Automation

Content Systems

Cadence needed high volumes of technical marketing content across product lines, regions, and languages, but their team was stretched thin. We built a generative AI pipeline that turns product specs into on-brand content variations for any channel or audience, with a human review step built in for quality control.

Cadence

3X

Production Speed

65%

Manual Work Reduction

Developed a generative AI system to automate large-scale content and data generation. The solution increased production speed by 3X, reduced manual workload by 65%, and improved output consistency across high-demand operational processes.

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Marcus V.

Chief Technology Officer, Cadence

LLM Services

Custom LLMs

RAG

LangChain

Fine Tuning

We develop and fine tune large language models tailored to your proprietary data, enabling intelligent automation, contextual understanding, and advanced reasoning capabilities. These systems are built to support enterprise-scale applications with accuracy, speed, and reliability.

UCLA

45%

Accuracy Improvement

60%

Faster Response Time

A UCLA research division was manually cross-referencing thousands of academic papers and clinical records, spending more time searching than researching. We built a custom LLM trained on their research corpus that answers multi-part queries, summarises findings across documents, and respects per-document access permissions for authorised researchers only.

Picture of Michael C.

Michael C.

Data Science Director, UCLA

We’ve Been Awarded Plenty for the
Milestones We Have Achieved