AI agents that
move your business forward.
We build custom AI agents that find answers, coordinate workflows, and take action across your existing applications—with people in control. Reduce manual coordination and give your teams more time for the work that matters.
Real workflows.
Practical AI.
From enterprise knowledge discovery to vendor support and facilities operations. These consulting examples distinguish deployed work, designs, and pilots; client names remain confidential.
Find the right report.
Trust the answer.
Built and deployed a Claude-powered report discovery agent that searches report definitions and requirements, explains the best match, suggests alternatives, and returns verified launch links without exposing underlying business data.
Turn incoming documents
into actionable requests.
Designed an AI-assisted intake workflow for scanned correspondence. It extracts and structures content into JSON, applies routing rules, and connects to the enterprise application to create tickets with human review.
Bring AI into the workflow
people already use.
Redirected a proposed chatbot after discovery revealed authentication and adoption barriers. Delivered a production solution within the existing vendor email intake process that retrieves relevant contract information and drafts email responses, with human review for accuracy, security, and approval before external communication.
Surface conflicts before
work overlaps.
Designed and built a monitoring MVP connecting enterprise real-estate, project management, and maintenance applications. A unified model and rules engine identified potential conflicts between capital projects and maintenance work; Claude was piloted as a controlled second-pass reviewer.
Have a workflow that could benefit from AI?
Explore it with us ↗Build a business
that works with AI.
Find the right opportunity, build the right AI solution, and give your teams a practical way to put it to work.
Agentic AI & automation
Design agents that retrieve context, use approved tools, and coordinate work across business systems. Scope permissions, human review, and exception handling around each workflow.
Explore agentic AI ↓AI copilots & applications
Give your teams AI experiences tailored to their work. Combine conversational interfaces, enterprise knowledge, and retrieval to help people find answers, create content, and make informed decisions.
Explore a custom AI solution ↗AI strategy & opportunity discovery
Identify workflows where AI could make a meaningful difference. Assess feasibility, prioritize opportunities, and define a focused pilot with clear success criteria.
Find your starting point ↓AI integration & operations
Connect agents to business applications and put them on a path to reliable operation, with evaluation, monitoring, access controls, and ongoing improvement.
Plan for production ↓From answering questions
to moving work forward.
AI agents bring reasoning, business context, and tools together to carry out multi-step work—with clear boundaries and people involved where decisions need judgment.
Receive a request
Capture an event, document, or business need.
Find the context
Retrieve trusted data and plan permitted steps.
Check the action
Apply policy checks and request approval when needed.
Complete & track
Use approved tools, log results, and route exceptions.
From incoming document to reviewed request.
Based on our document intake design. Open each step to follow a fictional facilities request; this example does not process documents or create real tickets.
01 · Receive
Sample letter: “Please arrange a roof inspection at Property 104. Water entered the stockroom after heavy rain.”
02 · Extract
The agent identifies the property, reported issue, affected area, and requested action. Missing or uncertain details are flagged.
03 · Classify
Business rules suggest a maintenance inspection request. Urgency and routing are checked against the organization’s policies.
04 · Review
A person checks the source document and proposed request, corrects details, and approves or returns it for clarification.
05 · Create & track
After approval, the intended workflow creates a ticket in the application and records its reference. Integration failures go to a person.
Connect to the tools your teams use.
Start with your existing APIs, databases, document stores, and business applications. Assess access and integration constraints before choosing the architecture.
AI Opportunity
Assessment.
Bring one workflow or a set of operational bottlenecks. We help you decide where AI can create useful, measurable progress.
Your opportunity shortlist
Review current work, identify repetitive handoffs, and rank candidates by value and feasibility.
A practical pilot plan
Define the recommended workflow, required integrations, access needs, and human approval points.
Clear success criteria
Agree how to evaluate quality, time saved, and task completion before committing to a broader rollout.
Scope, deliverables, timing, and fees are agreed before work begins.
Discuss an assessment ↗A clear path from
opportunity to operation.
We bring business owners and technical teams together to turn a useful AI idea into a tested workflow your organization can run and improve.
Assess the opportunity
Map your workflow, bottlenecks, data readiness, and risks. Choose a focused use case and define how success will be measured.
Design & validate
Prototype the workflow, connect relevant knowledge and tools, and test representative cases with your team.
Deploy with controls
Establish permissions, approval steps, logging, and exception handling. Validate quality before expanding access.
Measure & improve
Monitor task completion, quality, latency, and cost. Refine the system and transfer operational knowledge to your team.
Engineering experience. An AI-first future.
Enterprise experience.
Personal commitment.
JadeTech brings hands-on consulting and engineering experience across enterprise environments to its AI work. Our approach connects business needs with practical design, implementation, and delivery.
Our experience in cloud architecture and enterprise data supports that mission: giving AI solutions the reliable context, secure integrations, and operational foundations they need.
Start with clarity.
Practical questions about bringing agentic AI into your organization.
How is an AI agent different from a chatbot?
A chatbot primarily responds to a conversation. An agent can also use tools and follow a multi-step workflow, such as retrieving a record, drafting an update, and requesting approval before making a change.
What happens during the discovery call?
We discuss your current workflow, the bottlenecks your team faces, and where AI may help. You leave with an initial direction for a practical next step. The call lasts 30 minutes on Google Meet.
Where should we start?
Begin with a bounded workflow that has a clear owner, accessible data, and measurable outcomes. An opportunity assessment helps identify useful candidates and determine whether AI is appropriate.
Can agents work with our existing systems?
Integration depends on available APIs, permissions, and data access. We assess these during discovery and design around your existing environment where practical.
How do people stay in control?
Define what the agent can access and change, which actions need approval, and when work should be escalated. Evaluation, activity logs, and monitoring help teams inspect behavior and resolve failures.
How long does an engagement take, and what does it cost?
Scope, integration complexity, and validation requirements determine the timeline and cost. These are agreed after discovery, with milestones and success criteria defined before implementation.
Find your first
agentic AI opportunity.
In 30 minutes, we’ll discuss your workflow, identify where AI could help, and outline a practical next step.