AI services built around your workflows
Three ways we help growing businesses put AI to work. Each starts with a business problem, connects to the systems you already use, and keeps people in control of the decisions that matter.
Custom AI Agent Development
Agents that retrieve information, use tools, coordinate tasks, and assist employees with real workflows — within defined permissions and review boundaries.
The problem it solves
Your team spends hours gathering information from several systems before they can make a decision or reply to a customer.
Typical uses
- Answer staff questions using your own policies, manuals, and records
- Prepare a case file by pulling data from your CRM, inbox, and shared drives
- Draft replies or next steps for an employee to review and send
What you receive
- A working agent connected to the systems it needs, with scoped permissions
- Clear approval points wherever the agent would change data or contact someone
- Test cases and a short runbook your team can follow
Agentic Workflow Automation
Reduce repetitive work by connecting AI to email, documents, databases, CRMs, and internal business processes — with reliability, visibility, and appropriate approvals.
The problem it solves
Routine requests and documents arrive faster than people can sort, key in, and route them.
Typical uses
- Triage inbound requests and route each one to the right person
- Extract fields from invoices, forms, or orders and flag exceptions
- Keep records in sync across email, a CRM, and internal tools
What you receive
- An automated workflow with a human review step for exceptions
- Logging so you can see what was processed and why
- Monitoring and alerts when something needs attention
LLM Integration & AI Applications
Add language-model capabilities to the products and systems you already run: knowledge assistants, document intelligence, retrieval-augmented generation (RAG), and conversational interfaces.
The problem it solves
You want AI features in an existing product or internal tool without rebuilding it or exposing sensitive data.
Typical uses
- A knowledge assistant grounded in your company documents
- Summaries and search across contracts, tickets, or reports
- A conversational interface on top of an existing application
What you receive
- An integration built into your existing codebase or platform
- Evaluation tests that check answer quality before release
- Guidance on model choice, data handling, and running costs
How every system is built
People approve what matters
Agents work within defined permissions. Payments, outbound messages, and changes to production data go through a human approval step.
Your data stays handled with care
Access is limited to what each workflow needs, and data handling is agreed during scoping.
Tested before it is trusted
Every system ships with test cases and monitoring so you can see how it performs over time.
Also available
AI systems integration
APIs, CRM and ERP connectors, internal applications, databases, and event-driven workflows.
AI architecture & advisory
Opportunity assessment, framework selection, technical roadmap, security, evaluation, and cost planning.
Ongoing AI engineering
Support, monitoring, iterative improvements, and reliability work after launch.
Ways to work together
Paid discovery
A short, fixed engagement to map a workflow, assess feasibility, and produce a pilot plan.
Fixed-scope pilot
One well-defined workflow taken to a working system, with change control if the scope moves.
Ongoing engineering
A retainer for support, monitoring, and continued improvements once a system is in use.
Pricing depends on scope and is agreed before any paid work begins.
Have a process you want to automate?
Let's identify a practical AI opportunity and discuss the right first step.