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 bespoke machine learning solutions to automate complicated workflows, discover useful insights, and enhance decision-making. Each model is designed to be accurate, scalable, and easily integrated into real-world business settings.

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, one of our custom machine learning solutions, 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 build AI-driven high-performance web applications by combining robust backend architecture with user-friendly frontends. As part of our web application development services, 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 dated loan portal had users dropping off halfway through the application process and support teams were overwhelmed by simple questions. Through focused application development, we redeveloped it with an embedded AI assistant to guide clients through document submission, surface relevant products, and answer questions in real time, reducing 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, scalable, and highly available cloud infrastructures optimized for AI workloads with guaranteed performance. Our cloud migration services allow efficient deployment, monitoring, and scaling of standard ML models across dynamic enterprise environments.

Visualsoft

5X

Scalability

50%

Latency Reduction

Visualsoft’s AI rendering stack on-premise went down under peak sales traffic. They used cloud migration services to migrate their workloads to the cloud-native architecture with auto-scaling GPU clusters, edge caching, and cloud security services, supporting up to 40,000 concurrent requests and zero downtime, with no reduction in the quality of the render during peak traffic events.

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Emily R.

Director of Product, Visualsoft

Foundation Models

Hugging Face

Llama

Fine Tuning

Pretrained Systems

We tune and optimize large-scale foundation models for specific enterprise AI model deployment use cases. This approach cuts down development time without

Infotech

5X

Faster Deployment

40%

Efficiency Gain

It was a hard slog for Infotech engineers to work thru years of internal documentation and they would send repetitive questions to senior staff. In our enterprise AI model deployment process, we did foundation model fine-tuning over their entire knowledge base and integrated with their ticketing system. New engineers were up to speed in days. Senior staff weren’t pulled into unnecessarily escalated issues.

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Rebecca L.

VP of Engineering, Infotech

Generative Ai

OpenAI

Diffusion Models

Automation

Content Systems

Cadence’s team was spread thin, but they needed large volumes of technical marketing content across product lines, regions and languages. Our generative AI development services created a generative AI automation pipeline that takes product specs and generates on-brand content variations for any channel or audience. A human review step is built in for quality control.

Cadence

3X

Production Speed

65%

Manual Work Reduction

Built a generative AI automation system for large-scale content & data generation automation. The solution improved the speed of production by 3X, reduced the manual workload by 65%, and improved the output consistency across high-demand operational processes.

Picture of Marcus V.

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. Through Enterprise LLM integration, these systems are built to support enterprise-scale applications with accuracy, speed, and reliability.

UCLA

45%

Accuracy Improvement

60%

Faster Response Time

A research division at UCLA was spending more time looking than researching, manually cross-referencing thousands of academic papers and clinical records. We built a custom LLM trained on their research corpus with Enterprise LLM integration to answer multi-part queries, summarize findings across documents, and respect per-document access permissions for authorized researchers only.

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Michael C.

Data Science Director, UCLA

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