WHAT SETS US APART
We are a full-service firm bringing together UX, AI, data, and strategy to bring clarity, ethics, and usability to AI — so organizations can innovate with confidence and purpose.
Capabilities > AI Innovation
Our practice areas are designed to build on each other to create the ultimate competitive advantage in three steps, from the bottom up:
- First, we assess and structure your data across systems.
- Next, we help you create a knowledge architecture primed for use in a safe and secure AI architecture with optimal interoperability.
- Finally, we craft thoughtful user experiences designed to provide intuitive and actionable access to the right knowledge at the right time via AI interfaces.
Recent Work
Using AI to Understand Social Impact
We worked with The Rockefeller Foundation to design and implement an NLP-driven entity resolution and linking pipeline. The solution ingests unstructured grant data into a structured knowledge graph, enabling more accurate insights, reporting, and long-term impact analysis across funding initiatives. The outcome of our work resulted in more than 9M queryable relationships.
AI-Powered Knowledge Search
Working with the executives and engineers at Gryps, we conducted discovery research and redesigned the search experience for their document management platform. The new design integrates AI to improve document findability and uses semantic search, metadata, and knowledge graph techniques to support faster insights across complex construction workflows.
AI in Clinical Environments
We worked with a healthtech startup to conduct in-depth research and design an accessible, clinician-friendly user experience for their AI-powered diagnostic platform. The platform integrates multiple ontologies and data sources into a knowledge graph and uses LLMs to support point-of-care decision-making through diagnostic tools and AI copilots.
Our Services
AI Strategy and Planning
- Readiness Assessments: Evaluate organizational maturity and preparedness for AI adoption.
- Use Case Identification: Define feasible AI use cases aligned with ROI and business goals.
- Ethical AI Governance: Establish frameworks for responsible AI development and deployment.
Human-Centered AI Design
- UX/UI for AI-Powered Systems: Design interfaces focused on transparency, trust, and usability.
- Multi-modal UX: We help design multimodal interfaces where users can upload, annotate, compare, or generate content using image, video, and text inputs, integrated into unified AI flows.
- Custom Copilot and Assistant Design: We design copilot UX flows including onboarding, goal setting, memory management, and role definition, making AI assistants feel intuitive and context-aware across desktop or mobile experiences.
- Conversational AI: We design intelligent conversational interfaces that support exploration, discovery, and decision-making, with fallback patterns so users are never stuck inside a frustrating conversation loop.
- Workflow Integration: Design patterns that integrate with existing workflows and mental models.
- User Trust: Design systems that communicate AI outputs in ways users can understand and act on.
AI Data and Knowledge Architecture
- Data Preparation and Integration: Support data analysis, cleansing, and integration for AI readiness.
- LLM Evaluation: We define qualitative and quantitative methods for assessing LLM performance, including groundedness, usability, response time, and failure scenarios, informing model choice, confidence scoring, and interface design.
- Knowledge Graphs: Build semantic architectures for smarter AI-driven search and insights.
- Retrieval-Augmented Generation (RAG): Pipelines using vector stores, embeddings, and structured knowledge bases to ground LLM outputs in trusted internal content.
- Agentic AI: We design interfaces and reasoning flows for AI agents that collaborate with users and with each other. This includes prompt chaining, role assignment, and interface strategies to manage delegation, oversight, and multi-step decision-making.
- Prompt Engineering and Model Alignment: We collaborate with data scientists to design structured prompts and fine-tune LLM behavior. We test how prompt variations influence tone, accuracy, and output usefulness—especially in high-risk environments like healthcare or finance.
- Metadata and Data Mesh: Enhance data discoverability, governance, and interoperability with advanced metadata strategies.
Implementation and Optimization
- Prototyping and MVP Development: Rapidly test AI solutions through iterative prototyping and validation.
- Usability Testing and Iteration: Conduct user testing to refine AI systems for real-world use.
- Performance Monitoring: Establish metrics and dashboards to track AI performance and ROI post-deployment.
AI Education and Organizational Transformation
- Change Management: Create strategies to support teams in adopting and leveraging AI systems.
- Training and Workshops: Provide hands-on education for teams on using and managing AI ethically and effectively.
- Thought Leadership: Help organizations position themselves as leaders in principled AI innovation.
OTHER WAYS WE HELP ORGANIZATIONS
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