AI automation services and custom AI agents
We build custom AI agents and automation systems that connect your existing software, take on repetitive work, and run on cloud AI, private AI or locally deployed models. Your team stays in control of what matters, and the person who scopes your work is the person who does it.
Put repetitive work on autopilot
Your team should spend its time growing your business - not copying data between systems, answering the same questions, building reports by hand, searching through documents or doing repetitive administrative tasks.
We build custom AI agents and business automation systems that connect with the tools your company already uses and help automate everyday work.
Whether you need a cloud-based AI solution powered by leading AI models or a private AI system running inside your own infrastructure, we design the solution around your workflow, security requirements and business goals.
Automate the work. Keep your team in control.
Why work with us
- Custom solutions. Built around your actual process instead of forcing a generic platform.
- AI plus software integration. Connect AI to the systems employees already use.
- Cloud, private or hybrid AI. Architecture chosen for your technical and security requirements.
- Human oversight. High-impact actions stay under employee approval.
- Business first. Measurable value, not AI installed because it is popular.
What is an AI agent?
An AI agent is software that can understand a goal, analyze information, make decisions within defined rules, and take actions across your business systems. Instead of simply answering a question like a chatbot, an AI agent can help complete an entire workflow.
All of the steps in the example can happen while following the permissions, business rules and approval steps you define.
New to the term? Read a plain-language guide to AI agents for business.
For example, an AI agent could
- Read an incoming customer inquiry
- Identify what the customer needs
- Check your CRM
- Search approved internal documents
- Draft a response
- Create a CRM opportunity
- Assign the appropriate salesperson
- Schedule a follow-up
- Notify your team
What can we automate?
These are examples of workflows we can build. The right starting point is usually one task your team repeats every day.
Sales automation
- Qualify incoming leads
- Research prospects
- Update CRM records
- Draft personalized outreach
- Generate follow-up emails
- Summarize sales calls
- Create proposals
- Route leads
- Identify inactive opportunities
- Generate sales reports
Customer service automation
- Website AI assistants
- FAQ automation
- Ticket classification
- Automatic ticket routing
- Response drafting
- Order-status assistance
- Knowledge-base search
- Conversation summaries
- Human escalation
Email automation
- Read and categorize messages
- Extract important information
- Create CRM records
- Draft responses
- Route emails to the right team
- Identify urgent requests
- Generate follow-up tasks
- Summarize long threads
- Process attachments
Document automation
- Extract data from PDFs
- Process quotes and purchase orders
- Read invoices and forms
- Summarize contracts
- Classify technical documents
- Validate information
- Transfer data into another system
CRM automation
- Automatic lead creation
- Contact enrichment
- Opportunity updates
- Meeting summaries
- Follow-up reminders
- Pipeline analysis
- Lead scoring
- Next-action recommendations
Operations automation
- Data entry
- Scheduling
- Work-order processing
- Vendor communication
- Internal approvals
- Recurring reporting
- Procurement workflows
- Project coordination
Internal AI knowledge assistant
Give employees a controlled way to ask questions about your company's information. A knowledge assistant can retrieve from authorized SOPs, manuals, policies, technical documentation, product specifications, training materials, contracts and internal knowledge bases.
Instead of searching through folders for 20 minutes, an employee could ask, "What is our procedure for handling this customer request?" The system retrieves the relevant approved information and returns a grounded answer.
Looking for more ideas? See 25 business processes you can automate with AI.
AI agents that work with your existing software
Your company should not need to replace every system it already uses just to adopt AI. We can design integrations with systems such as the ones listed here.
If your software provides an API or another reliable integration method, it may be possible to incorporate it into an automated workflow.
Our AI integration services page covers connecting AI to CRM, ERP and document systems in more detail.
Systems we can connect
- CRM platforms
- ERP systems
- Microsoft 365
- Google Workspace
- Slack or Teams
- Accounting software
- Databases
- APIs
- Cloud storage
- Websites
- Customer portals
- Internal software
- Custom applications
Cloud AI or private local AI
Not every business should use the same AI architecture. We help determine which approach makes sense based on your data, security requirements, performance needs, infrastructure and budget.
Cloud AI
Cloud AI can use leading commercial models for language understanding, reasoning, document processing, analysis and automation. It is often a strong fit when the priority is high model capability, fast deployment, scalability and lower infrastructure overhead.
We can build OpenAI-powered applications and automations when commercial cloud AI is the right fit. We evaluate the workflow, data sensitivity, permissions, retention needs and required controls before recommending an architecture.
Private or local AI
Some organizations want more control over where information is processed. We can design AI systems using models that run within your server, private cloud, data center, dedicated infrastructure or approved company hardware.
- Greater control over data location
- Customized security architecture
- Reduced dependence on a single external AI provider
- Model customization
- Internal knowledge integration
- Greater control over infrastructure and retention
Local AI vs. cloud AI: which is better?
There is no universal answer. Cloud AI is often better when you need advanced models, rapid implementation and easy scalability. Local AI may be better when infrastructure ownership, data-location requirements, offline operation or internal security controls are the priority. A hybrid architecture can combine both.
Private AI is a control and architecture option, not automatically safer than cloud AI. Security depends on configuration, access controls, network design, logging, software updates, model governance and operating practices.
Read the local AI vs. cloud AI comparison, when to choose OpenAI or a local model, or see how our private AI work is set up.
Keep your team in control
Automation does not have to mean giving AI unlimited authority. We can design workflows where AI performs the repetitive work while employees retain control over important decisions.
Human approval is recommended whenever an incorrect action could create meaningful financial, operational, legal, safety or customer consequences.
- AI receives the request
- AI analyzes it
- AI prepares the action
- An employee approves
- The system executes
Actions we suggest keeping behind an approval step
- Sending external messages
- Changing customer records
- Creating orders
- Issuing quotes
- Financial actions
- Updating important databases
- Other sensitive or high-impact actions
Examples of AI agents we can build
Each agent works only with the tools and data you allow, and sensitive steps can wait for a person's approval.
Research prospects, qualify leads, draft outreach, update the CRM and schedule follow-ups.
Answer common questions from approved knowledge and escalate complex issues.
Read, classify, summarize, route and draft replies.
Extract information from invoices, forms, purchase orders and PDFs.
Coordinate recurring operational activities across internal systems.
Collect data from multiple sources and prepare management reports.
Answer employee questions from authorized internal content.
Coordinate meetings, reminders and follow-ups.
Keep records updated and recommend next actions.
Designed around a unique business process.
How our AI automation process works
- 1AI opportunity assessment
Identify repetitive work that may be appropriate for automation.
- 2Workflow mapping
Document users, inputs, systems, decisions and approval steps.
- 3ROI prioritization
Rank opportunities by time saved, volume, complexity, risk and potential return.
- 4Prototype
Build a focused solution around one clearly defined workflow.
- 5Integration
Connect the required applications and data sources.
- 6Testing and safeguards
Test outputs, permissions, exceptions, failure modes and human approval requirements.
- 7Deployment
Introduce the system into the real workflow.
- 8Monitoring and improvement
Evaluate accuracy, cost, usage, errors and changing business requirements.
Start small. Prove the ROI. Then expand.
A successful AI strategy often starts with one repetitive workflow instead of trying to automate an entire company at once.
Before
Employee receives email, opens the attachment, copies the data, enters it in the CRM, creates a task and sends a confirmation.
After
AI reads the email, extracts the attachment data, prepares the CRM record, creates the task and drafts the confirmation. An employee reviews where required.
Example workflow, shown for illustration.
Ways to work with us
Most businesses start with an assessment of one workflow. The other options follow when there is something to build or run.
AI Automation Assessment
Best for: Companies unsure where to start.
Includes: Workflow review, automation opportunities, ROI estimate, risk review, architecture recommendation and a roadmap.
Request an assessmentCustom AI Automation
Best for: One defined workflow.
Includes: Agent or workflow build, integrations, testing, approval logic, deployment and documentation.
Automate this workflowEnterprise and Private AI
Best for: Security- or infrastructure-sensitive organizations.
Includes: Private or local AI, retrieval over your documents, access controls, audit logging, model evaluation and custom integrations.
Talk about private AIManaged AI Operations
Best for: Businesses that want ongoing ownership.
Includes: Monitoring, prompt and workflow updates, model changes, error review and usage and cost optimization.
Discuss supportIndustries we can support
These are examples of businesses where the same patterns apply. They are not a client list.
- Manufacturing
- Industrial automation
- Engineering companies
- Construction
- Automotive
- Professional services
- Real estate
- Logistics and distribution
- Healthcare administration
- Technology
- Retail
- Field services
- Small and midsize businesses
Examples of what could be automated
Manufacturing and industrial
- Turn RFQs and technical emails into structured opportunities
- Search product manuals and internal technical documentation
- Summarize service reports
- Automate vendor and customer follow-up
- Generate production or operations reports
- Assist with part cross-reference and approved product information
Engineering companies
- Search standards, specifications and project files
- Draft project summaries
- Automate document classification
- Generate recurring project reports
- Assist with proposals and scope documents
- Route technical requests
Automotive and dealerships
- Lead response and qualification
- Inventory content generation
- CRM follow-up
- Customer question routing
- Appointment scheduling
- Document extraction and listing workflows
Professional services
- Client intake
- Document summarization
- Knowledge search
- Proposal drafting
- Meeting notes and follow-ups
- Recurring reporting
Construction and field service
- Work-order intake
- Job documentation
- Inspection summaries
- Scheduling and dispatch support
- Estimate intake
- Field report processing
How much does AI automation cost?
Cost depends on workflow complexity, integrations, model choice, infrastructure, security requirements, transaction volume, support expectations and the level of customization. A focused workflow using existing APIs can be much simpler than an enterprise agent connected to multiple databases, legacy applications, private infrastructure and custom identity controls.
We recommend starting with the smallest practical implementation that can prove value, then expanding once the workflow shows measurable results.
For a longer explanation, read how much AI automation costs and what drives it.
What does this work cost today?
Example Example figures - replace with your own.
Loaded cost means wages plus payroll taxes and benefits. Current annual cost = employees x hours per week x hourly cost x 52.
- Savings at 25% automated
- $10,920
- Savings at 50% automated
- $21,840
- Savings at 75% automated
- $32,760
- Savings at your figure (50%)
- $21,840
Illustration only. This is arithmetic on the figures you enter, not a quote, a forecast or a guarantee of savings, and it leaves out build and operating costs. Nothing you type here is sent anywhere.
Frequently asked questions
Find out what your business can automate
Answer a few questions about one repetitive task. They make us think about a measurable workflow before the first call, and we will tell you honestly whether it is a good candidate.
An AI Automation Assessment covers
- Workflow review
- Automation opportunities
- ROI estimate
- Risk review
- Architecture recommendation
- A roadmap