AI built into the workflow, not added as a disconnected chatbot
We build AI-powered software where intelligence participates directly in the product workflow: understanding documents, evaluating user input, retrieving company knowledge, assisting decisions, generating structured outputs, or automating repetitive work.
The AI layer is designed together with the application, permissions, data model, audit requirements, and user experience so it can become a useful product capability rather than a novelty.
AI capabilities we build
- Retrieval-augmented generation (RAG)
- Organization-specific knowledge assistants
- Document analysis and summarization
- OpenAI, Claude, and Gemini integrations
- Multi-model AI experiences
- AI-powered search and knowledge retrieval
- AI-assisted writing and speaking evaluation
- Workflow automation and guided onboarding
- Structured extraction from files and text
- AI research workspaces
- Context-aware conversational assistants
- AI-ready APIs and application architecture
RAG and private knowledge workflows
For systems that need answers grounded in company material, we build retrieval workflows around documents, procedures, internal knowledge, or user-provided sources. This makes the assistant respond from the relevant context instead of relying only on generic model knowledge.
AI assessment, analysis, and intelligent feedback
We have developed learning workflows where written and spoken responses are sent through AI evaluation layers and returned with scoring, feedback, and improvement guidance.
We have also built products where AI reasons across uploaded files, videos, notes, market information, and grouped research content so users can work with a richer context than a standalone prompt.
Selected experience
- Built an AI-assisted trading research platform combining OpenAI, Claude, Gemini, documents, audio, YouTube research, charts, versioned strategies, subscriptions, and credit-based AI usage.
- Built an organization-specific RAG assistant for field technicians so users could query company manuals, procedures, and technical instructions while working. Client identity is confidential.
- Built AI-assisted onboarding and workflow automation into a behavioral-health operations platform so AI could help progress real administrative workflows. Client identity is confidential.
- Built Moodle-based exam workflows using AI for writing evaluation, speech transcription, speaking assessment, personalized feedback, and adaptive practice.
Production AI needs more than a model API
The surrounding application matters just as much as the model. We combine AI services with secure application logic, databases, vector or retrieval workflows, permissions, background processing, observability, and interfaces designed around the actual task.
Frequently Asked Questions
Can you integrate multiple AI models?
Yes. We have built multi-model workflows using OpenAI, Claude, and Gemini where users or the application can select the appropriate model.
Can AI work with our private documents?
Yes. RAG and document-retrieval architectures can ground responses in approved organization-specific content.
Can you add AI to an existing application?
Yes. We can introduce AI through APIs and background services without rebuilding the entire application.
Do you build AI features beyond chat?
Yes. Our work includes assessment, document processing, summarization, workflow automation, onboarding, structured extraction, research workflows, and contextual guidance.
Have an AI product or workflow in mind?
We can help determine where AI adds real value, how it should connect to your data and product, and what needs conventional engineering around it.