AI strategy, custom systems, and workflow automation.
CitronLab helps businesses turn AI ideas into working systems. We start with the workflow, not the model. Then we design and build the software around your data, users, rules, and required outputs.
Find the AI opportunities that are actually worth building.
Not every workflow needs AI. Some need better data structure, better software, better process, or a smaller automation. We help identify the places where AI can make the work faster, clearer, more searchable, more consistent, or more scalable.
- Workflow mapping
- Data-source inventory
- AI opportunity assessment
- Build recommendation
- Risk and governance notes
- Initial product architecture
- Integration planning
- Proof-of-concept scope
Build the product your workflow needs.
We build custom AI software for businesses whose needs do not fit neatly into off-the-shelf tools. That may mean an internal operating system, client portal, review workflow, search assistant, document intelligence layer, reporting engine, or customer-facing AI product.
- AI search over company data
- Document review and compliance systems
- AI-assisted report generation
- Customer-facing AI assistants
- Internal operations platforms
- Private knowledge systems
- AI-powered dashboards and review queues
- Client portals and workflow tools
Put AI inside the work, not beside it.
AI becomes useful when it is connected to what happens next. We build systems that move work forward: classify the document, draft the report, create the task, update the record, show the source, flag the exception, notify the right person, and preserve the review trail.
- Document intake and classification
- Report and deliverable generation
- Review queues and approvals
- Alerts and digests
- Workflow-triggered summaries
- System-to-system integrations
- Audit-ready exports
- CRM, finance, email, database, and API integrations
Designed for control.
AI systems need boundaries. We design for permissioning, logging, cost tracking, data retention, source citations, human review, and private architecture from the start.
RAG and knowledge systems
Indexed, cited retrieval over your data — not generic context windows.
LLM workflows
Models composed with deterministic logic, not used as a single magic step.
Agentic AI
Where it makes sense — bounded, observable, and reversible.
OCR and extraction
Vision OCR, classification, and structured extraction from messy documents.
Embeddings & semantic search
Hybrid keyword + vector retrieval for explainable answers.
Private / on-device AI
Local-first or private-cloud where data sensitivity demands it.
Integrations and APIs
Connectors into the systems your business already runs on.
Audit trails & review workflows
Reasoning chains, usage logs, and human approvals built in.
AI usage & cost tracking
Per-user, per-feature visibility so AI does not become a runaway line item.
Want to know what this could look like in your business?
Tell us what you are trying to build, automate, understand, or improve. We'll help you decide what is worth building and what the first version should look like.