Engineer AI into the way your business works.
AI creates value when it moves beyond the model and becomes part of the systems, data and workflows your business already depends on.
Margins designs and builds production AI systems around your operations — from models and data pipelines to enterprise integrations, applications and infrastructure.
The model is only one part of the system.
Production AI requires more than AI.
A model can perform brilliantly in isolation and still fail to create value inside a real business. It needs access to the right data. It needs to understand business rules. It needs to connect to existing systems. People need a practical way to interact with it. Exceptions need somewhere to go. Performance needs to be monitored. And the entire system needs to remain reliable as the business changes.
That is the engineering problem we solve.
- 01AILLMs · Machine Learning · Computer Vision · Voice
- 02DataPipelines · Vector databases · Enterprise data · Documents
- 03SoftwareApplications · Interfaces · APIs · Backend systems
- 04IntegrationERP · CRM · Internal systems · Third-party platforms
- 05InfrastructureCloud · Private cloud · On-premises · MLOps
- 06OperationsMonitoring · Evaluation · Observability · Improvement
The right technology for the problem.
Generative AI & LLM Systems
Production applications built around language models, enterprise data and real business workflows.
Explore Enterprise AIAI Agents
AI systems capable of reasoning across information, using tools and executing multi-step business workflows.
Explore AI AgentsEnterprise Knowledge & RAG
Make proprietary business knowledge accessible and usable by AI without relying solely on what a generic model already knows.
Explore Enterprise Knowledge & RAGPredictive AI & Machine Learning
Use historical and operational data to anticipate what is likely to happen next.
Explore Predictive AIComputer Vision
Turn images and video into structured information and operational actions.
Explore Computer VisionVoice AI
Natural-language interfaces that can understand, process and act on spoken information.
AI belongs inside the operation.
The most valuable enterprise AI systems rarely operate alone. They need to understand what is happening across the business and act through the systems the company already uses.
Margins engineers AI around your existing technology environment rather than forcing the business to operate around the AI.
ERP & core systems
Connect AI to the operational source of truth.
CRM & customer platforms
Bring intelligence directly into commercial workflows.
Data infrastructure
Work across structured and unstructured enterprise data.
Internal software
Integrate with proprietary systems, APIs and workflows.
A prototype proves something can work. Production proves it can work every day.
Production AI has to survive things demos don’t.
We make these questions part of the architecture — not problems left for after launch.
From business case to production architecture.
Our engineering responsibility doesn’t end at deployment. Margins can continue operating, monitoring and improving the system through Forward Deployed Engineering and Managed AI.
- 01
Define success
Translate the business objective into measurable system requirements.
- 02
Architect
Define models, data, integrations, software, infrastructure and operational boundaries.
- 03
Validate
Prove the highest-risk technical assumptions early.
- 04
Engineer
Build the AI system and the software around it.
- 05
Integrate
Connect it to enterprise data, systems and workflows.
- 06
Productionize
Deploy, monitor, evaluate and establish operational controls.
- 07
Iterate
Measure what happens in the real business and improve from there.
Build AI without giving away what makes your business valuable.
Your proprietary data, processes and organizational knowledge are increasingly part of your competitive advantage. We design enterprise AI so that control over those assets stays where the business needs it.
Your cloud
Deploy into the customer’s existing cloud environment and technology stack.
Private infrastructure
Build within isolated, customer-controlled environments.
On-premises
Deploy locally where operational, regulatory or data requirements demand it.
The objective isn’t to move your business into somebody else’s AI environment. It’s to bring AI into yours.
We don’t start every AI system from zero.
Enterprise AI implementations repeatedly need the same underlying capabilities: connecting models and data, orchestrating workflows, applying business rules, monitoring execution and operating reliably over time. That’s why we built Rivermind.
Rivermind is the operational layer behind enterprise AI. Margins uses it to accelerate custom implementations and provide the orchestration, integration and operational control required once AI moves into production.
Explore Rivermind (opens in a new tab)The people who scope the system understand how to build it.
Complex AI implementations lose momentum when strategy, architecture, data, software and AI are handed between disconnected teams. Margins brings those disciplines together.
AI & ML Engineers
Models, agents, RAG, computer vision and predictive systems.
Software Engineers
Production applications, APIs and backend systems.
Data Engineers
Pipelines, enterprise data and AI-ready infrastructure.
Cloud & DevOps Engineers
Deployment, infrastructure, observability and reliability.
UX & Product
Interfaces that make AI useful inside actual workflows.
Need more than engineering?
You don’t need to arrive with a technical specification. Margins can start before the solution has been defined and stay after it enters production.
AI Strategy & Consulting
Identify the right opportunity and define the business case.
Explore AI Strategy →AI Engineering
Design and build the production system.
You are hereManaged AI
Operate, monitor and continuously improve it.
Explore Managed AI →From AI strategy to AI in production. One partner.
Have an AI opportunity that needs to become real?
Whether you have a defined specification, an early concept or simply a business problem you believe AI can solve, we’ll help determine the right technical path to production.
Talk to an AI EngineerStart with the problem. We’ll work out the architecture.