Start with the workflow, then build the application.
Five questions to ask before turning an operational challenge into software.
Read the guideAI strategy, machine learning, generative AI, data engineering, and cloud consulting. We connect the possibilities to the way your business works—from small teams to midsize organizations, across industries.

From your first AI roadmap to models, applications, and data platforms in production. Explore the full range of Isospins services.
Turn a defined business question into a testable machine learning solution. Explore predictive analytics, natural language processing (NLP), and computer vision, with evaluation, model training, and cloud integration planned around the intended workflow.
02Design useful generative AI experiences for content, knowledge, product design, and document workflows. Scope large language models (LLMs), synthetic data, fine-tuning, and agentic AI around approved information, bounded actions, evaluation, and human review.
03Build the data foundations behind analytics and AI. Plan and implement ETL/ELT pipelines, cloud warehouses, data lakes, and real-time or batch processing, with explicit ownership, quality checks, access requirements, and operational documentation.
04Decide where AI belongs in your organization and what to do first. Connect readiness, use-case prioritization, technology choices, change management, and training in a practical adoption roadmap, including agentic AI opportunities where actions and responsibilities can be clearly defined.
05Connect AI applications, APIs, and model hosting across AWS, Azure, and Google Cloud. Scope multicloud architecture, platform integration, security and compliance requirements, operational responsibilities, performance, and cost against the needs of the application.
Architecture, application modernization, and operational readiness.
Patient experiences, staff tools, and connected workflows.
Have an early idea or a challenge that spans these services?
Start with a discovery conversationBring the context of your industry to AI, data, cloud, and application decisions.
Explore healthcare applications and AI support for patient engagement, clinical information review, and operations. Define data access, integration, evaluation, and professional review around each workflow before implementation.
Explore the possibilitiesExplore AI support for banking and insurance workflows, from transaction review to advisory preparation and claims administration. Scope access, traceability, evaluation, and qualified human review for financial recommendations and consequential decisions.
Explore the possibilitiesExplore document, research, and knowledge workflows for legal and professional teams. Connect approved sources to focused AI assistance, with confidentiality requirements, source inspection, and professional judgment built into the scope.
Explore the possibilitiesExplore AI experiences for product discovery, customer support, and merchandising operations. Connect catalog, order, and inventory information to focused applications, with clear business rules and staff ownership.
Explore the possibilitiesExplore AI support for equipment planning, supply-chain coordination, and product intelligence. Bring operational data and staff knowledge into scoped applications with evaluation, system boundaries, and defined decision ownership.
Explore the possibilitiesExplore AI and application opportunities across public services, learning, and energy operations. Define the users, information boundaries, evaluation criteria, and accountable human decisions for each setting.
Explore the possibilitiesExplore an enterprise knowledge assistant, a healthcare application workflow, and cloud operations visibility. Three examples from a broader consulting practice.
A simple queue for a team's next action.
Select a sample record to explore the workflow.
A knowledge assistant grounded in approved material.
Illustrative application resource usage.
Clear scope. Visible progress. Thoughtful decisions at every step.
Define the people, workflows, constraints, and outcome that matter.
↗ A shared problem statementMap the experience, choose the architecture, and agree on a useful first release.
↗ A practical delivery planDevelop in visible increments, with feedback and testing along the way.
↗ Working software to reviewPrepare deployment, document the handover, and prioritize what comes next.
↗ A foundation to build onWe bring AI consulting, data engineering, application development, and cloud expertise into one conversation. Our starting point is the business problem you want to solve.
That means asking better questions, making technical choices explicit, and shaping a first release you can understand and review.
Get to know IsospinsFive questions to ask before turning an operational challenge into software.
Read the guideA practical way to narrow the use case, define review, and evaluate value.
Read the guideHow to bring application needs, operational risk, and cost into one plan.
Read the guideYes. We can start with discovery: identify the users, map the workflow, explore technical constraints, and define a practical first release. You do not need a complete specification to start the conversation.
We can review the application, its architecture, and the changes you need. That review helps define whether to improve specific parts, add integrations, or plan a broader modernization.
We assess AI against the task, available information, and expected benefit. The recommendation follows the problem. Straightforward software and automation can often provide the right foundation.
Our industry practices cover healthcare and life sciences; banking and insurance; legal and professional services; retail and e-commerce; manufacturing and supply chain; and government, education, and energy. Healthcare app development is one practice within our wider AI, data, and cloud consulting business.
Data flows, access controls, retention, and relevant contractual requirements are part of project discovery. Our public demonstrations use synthetic data. Please keep patient information out of project inquiries.
They depend on the application, integrations, and delivery requirements. The proposed engagement should set out deliverables, responsibilities, milestones, and pricing before implementation begins.
Start with one recurring task, one team, and a scope you can evaluate. Connect AI, reporting, and cloud decisions to the way your business operates.
Help your team find approved information, organize incoming documents, and prepare work for review. Start with one document type or one knowledge workflow, with source access and human decisions clearly defined.
Explore this starting pointBring selected business systems into a reporting workflow your team can understand and maintain. Start with one recurring decision, the information behind it, and clear definitions for the numbers being reviewed.
Explore this starting pointConnect cloud spending to the applications and business activity it supports. Review one environment or workload, identify changes worth assessing, and plan modernization with operational ownership and rollback in view.
Explore this starting pointStart a conversation about your application, AI opportunity, or cloud environment.