01
AI agents & copilots
Controlled agents that retrieve knowledge, use tools, and move work forward with human approval where it matters.
- Tool use
- Human review
- Audit trails
Enterprise AI engineering
Turn complex operations into working AI systems.
DotSquare AI designs and engineers production-ready agents, knowledge systems, and intelligent workflows for teams moving beyond AI experiments.
Security-aware architecture Integration-first delivery Evaluation before scale
AI operations / workflow 04Illustrative system
Enterprise request
Orchestration layer
Policy gate
01 / RETRIEVEKnowledge contextPermission-aware sources
02 / REASONModel routingTask-specific selection
03 / VERIFYEvaluation checksQuality threshold passed
04 / APPROVE Human checkpointReady for controlled action
Built for production
LLM applications
Agent orchestration
RAG systems
Computer vision
MLOps
What we build
AI capabilities shaped around the operation—not the demo.
We combine product thinking, AI engineering, and systems integration to deliver tools people can trust in real workflows.
02
Enterprise knowledge systems
Grounded search and RAG experiences that connect fragmented documents, applications, and operational data.
- Hybrid retrieval
- Citations
- Access control
03
Intelligent automation
Adaptive workflows for document-heavy, exception-rich processes that brittle rules cannot handle well.
- Orchestration
- Exceptions
- Integrations
04
Vision & document AI
Multimodal systems that turn images, forms, invoices, and PDFs into structured, reviewable information.
- Extraction
- Classification
- Validation
How engagements begin
Start with the operation. Then choose the intelligence.
We map the people, decisions, systems, exceptions, and evidence around a workflow before prescribing technology. It keeps the first release focused and makes adoption part of the architecture.
Plan an opportunity workshopBuilt for accountable delivery
From first use case to an operated system.
AI value depends on more than model choice. We design the surrounding product, data, controls, and feedback loops needed for dependable use.
Plan an opportunity workshop- 01
Opportunity mapping
Define the decision, workflow, users, constraints, and evidence required for a useful first release.
- 02
Architecture & prototype
Validate the riskiest assumptions with representative data and an integration-aware technical design.
- 03
Production engineering
Build the product, evaluation suite, guardrails, observability, and enterprise integrations together.
- 04
Deploy & improve
Release with measurable quality thresholds, operational ownership, monitoring, and an optimization roadmap.
Engineering principles
Clear controls. Observable quality. Practical ownership.
Security by design
Role-aware access, data boundaries, and deployment choices are considered from architecture—not appended at launch.
Evidence-led evaluation
Representative test sets and release thresholds make quality visible before workflows depend on it.
Designed to integrate
APIs, identity, approval paths, and existing systems shape the solution from the beginning.
Your next AI system
Start with the workflow that matters most.
Bring us a process, product idea, or operational bottleneck. We’ll help frame a focused path from opportunity to production.
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