How We Work
Our Approach
We believe in understanding your data before building solutions, and proving value through experiments before scaling.
Data Discovery
Before building any AI solution, we start with a deep understanding of your data landscape. Data Discovery is our systematic process for assessing your data sources, quality, accessibility, and potential.
We examine what data you have, how it flows through your organization, where the gaps are, and what opportunities exist for AI to create value. This foundation ensures every solution we build is grounded in real, valuable data — not assumptions.
What we assess:
- Data sources — databases, APIs, spreadsheets, CRMs, ERPs, and unstructured data stores
- Data quality — completeness, consistency, freshness, and accuracy across systems
- Accessibility — how data flows between systems, integration readiness, and API availability
- AI potential — which datasets are most valuable for machine learning, automation, and intelligent workflows
The result is a clear map of your data landscape and a prioritized list of AI opportunities ranked by feasibility and business impact.
Experiments First
We believe in proving value before committing to full-scale implementation. Our Experiments First approach prioritizes rapid prototyping and proof of concept — delivering quick wins that demonstrate feasibility and ROI.
Each experiment is a focused, time-boxed effort designed to answer a specific question about what AI can do for your business. Successful experiments become the building blocks for production solutions.
How it works:
- Define the hypothesis — we identify a specific, measurable question AI can answer for your business
- Build fast — a focused proof of concept in days, not months, using real data from your Discovery phase
- Measure outcomes — we evaluate accuracy, speed, cost savings, and user experience against clear success criteria
- Decide together — results inform whether to scale, pivot, or explore a different approach entirely
This approach eliminates the risk of building the wrong thing. You invest in full-scale development only after seeing proof that the solution works with your data.
Our Process
Discovery
We start by understanding your business, data, and goals through our comprehensive Data Discovery process.
Experiment
We build rapid proof-of-concept experiments to validate AI approaches and demonstrate value quickly.
Build
Validated experiments become production-ready solutions with enterprise-grade security and scalability.
Deploy
We deploy your AI solution in your environment — cloud, on-premises, or hybrid — with full support.
Optimize
Continuous monitoring and optimization ensures your AI solution improves over time and adapts to changing needs.
Frequently Asked Questions
We work across a wide range of industries including healthcare, manufacturing, financial services, retail, education, and technology. Our AI solutions are adaptable to any industry with data-driven challenges.
Project timelines vary based on complexity and scope. Our Experiments First approach starts with rapid proof-of-concept work, so you see results quickly. Full implementations typically follow an iterative process with regular milestones.
We are model-agnostic and work with the best tools for your specific needs. This includes models from Anthropic (Claude), OpenAI (GPT), open-source alternatives, and custom-trained models. We recommend the right approach based on your requirements.
Data security is paramount. Our solutions support SOC 1/2/3, ISO 27001, and HIPAA compliance. We offer containerized, on-premises deployments for sensitive data and ensure all data handling follows enterprise security best practices.
iNtuition is our flagship AI execution environment. It provides professional user personas, custom prompt templates, data integration, and containerized deployment. It connects to your business data sources and enables teams to chat with data, generate reports, and leverage AI in their daily workflows.
Yes. We support cloud, on-premises, and hybrid deployments. Our containerized architecture makes it straightforward to deploy in any environment that meets your security and compliance requirements.
Data Discovery is our systematic approach to understanding your data landscape before building AI solutions. We assess your data sources, quality, accessibility, and potential, ensuring any AI solution we build is grounded in real, valuable data.
Experiments First is our approach to AI development that prioritizes rapid prototyping and proof of concept before committing to full-scale implementation. We believe in proving value quickly through focused experiments that demonstrate feasibility and ROI.
The best way to get started is to schedule a free consultation. We will discuss your business challenges, data landscape, and AI opportunities. From there, we can propose a tailored approach that fits your needs and budget.
Now You Know How We Work
Your data is probably already telling us what to build. Let's listen.