AI Services

Custom AI agent
development Services,
built for the specific process consuming your team’s time.

Custom AI Agent — How It WorksAnimated vertical pipeline showing four sequential stages of how a custom AI agent operates.Custom AI AgentRead · Act · EscalateYour SystemsLive ERP, CRM, or platform dataAgent Reads DataIdentifies the work in the queueApplies Rules, ActsDefined action taken automaticallyHuman EscalationExceptions routed with context
01. What This Service Does

Built for the Process You Cannot Stop Managing Manually

Tayana builds custom AI agents for defined, high-volume operational processes that currently require manual coordination, follow-up, and escalation to function. The agent handles the repeatable logic. Exceptions reach the right person with context already assembled. Your existing systems stay exactly where they are.

Most operational bottlenecks are not technology gaps. The data already exists in your ERP, your CRM, or your operational platform. What falls between systems is the coordination work: a collections queue worked by hand each morning, a back order that requires contact with three parties before it resolves, a vendor invoice that does not match and waits in a folder until staff have time for it. Where agentic AI for business operations delivers the most measurable value is precisely in that space: the repetitive decision work that consumes qualified staff time without requiring genuine judgment on every iteration. An AI agent reads your data, applies your business rules, takes the defined action, and escalates what actually requires a human.

Each agent is built for your specific workflow, not configured from a template. Tayana's AI agent development services cover the full scope from process discovery through pilot deployment. The engagement does not close until the agent is running on your real data, in your real environment.

02. Who This Is For

Who Needs It and Who Does Not

Good fit
Not a good fit
A Good Fit
Not a Good Fit
Good FitYou have a specific, high-volume process where staff spend significant time on coordination or exception handling that follows defined rules most of the time.
Not a Good FitThe process does not have consistent rules. If decisions vary in ways that cannot be articulated, an agent will not perform reliably.
Good FitYour systems have API access that allows an agent to read and act on live data.
Not a Good FitYour systems do not have API access and your IT environment does not permit integration work.
Good FitYou can describe the process and its decision points, even if they have never been formally documented.
Not a Good FitYou want a pre-built product that can be configured in a day. This is an engineering engagement, not a software subscription.
Good FitYou are ready to start with one process in a controlled pilot before expanding.
Not a Good FitThe process involves regulated advice, medical determinations, or legal decisions requiring human review at every step.
Good FitSomeone on your team can commit 8 to 12 hours across discovery and testing.
Not a Good FitYour team cannot dedicate time to discovery and validation.
03. The Process

How It Works

1

Process Discovery

Two to three sessions with the staff who handle the work today. We map the full workflow, decision points, systems involved, and where human judgment is genuinely required. One to two weeks. Both parties sign off before development begins.

2

Integration Assessment

We review your API documentation, confirm connectivity, and establish how the agent will read from and write back to your environment. Integration feasibility is confirmed before any development cost is committed.

3

Agent Specification

We document exactly what the agent does autonomously, what it escalates, and what it will not touch without approval. You review and approve this before development begins.

4

Development and Integration

The agent is built and connected to your systems, tested against real scenarios drawn from your actual process data.

5

Validation Testing

You test the agent against your own data. Your team adds edge cases. Anything that does not behave as expected is corrected before the pilot begins.

6

Pilot Deployment

The agent goes live on a controlled scope. Your team monitors outputs for two to four weeks. Rule adjustments happen during this window based on live observation.

7

Handoff and Documentation

You receive full operational documentation and a handoff session with whoever owns the process going forward.

04. Deliverables

What the Client Receives

05. Scope and Cost

Timeline and Investment

Timeline

6 to 8 Weeks

From first conversation to pilot-ready agent. Discovery and integration assessment take the first two weeks. Development and testing run through weeks three to five. Pilot deployment and observation cover weeks six to eight.

Investment

From $10,000

Investment for a single-process pilot. Scope, integration complexity, and voice requirements determine the final cost. A detailed estimate is provided during integration assessment, before any development commitment is made.

Ongoing platform costs for AI processing and workflow infrastructure typically run $100 to $1,000 per month. A detailed estimate is provided during integration assessment, before any development commitment is made. This is AI workflow automation consulting, not a subscription where costs are hidden until you are already committed.

06. Questions

Common Questions

How is a custom AI agent different from the automation features already in my ERP or CRM?+

Your ERP vendor builds features that work across thousands of companies. A custom agent applies your specific business rules, your escalation thresholds, and your exception logic. The difference is most visible in edge cases, which is where your staff currently spends the most time.

What processes are the best candidates for AI agent automation?+

High-volume processes with defined decision rules and predictable escalation paths: AR collections, AP invoice matching, back order coordination, return processing, and order exception handling. The common factor is that the process generates the same types of decisions repeatedly, most of which follow a describable pattern.

Do I need to replace or upgrade my existing systems first?+

No. The agent integrates with what you are running now. API access or a reliable data path from your current systems is what is required. Integration feasibility is confirmed in the first two weeks, before any development cost is incurred.

What happens if the agent makes a wrong decision?+

Every agent is built with human escalation as a structural requirement. Decisions outside defined thresholds go to a human reviewer before action is taken. The pilot period exists specifically to surface and correct edge case behavior before full deployment.

How much of my team's time does this engagement require?+

Discovery takes 4 to 6 hours across two to three sessions. Validation testing takes another 4 to 6 hours. Pilot monitoring requires 2 to 4 hours per week for the first four weeks.

Can the agent handle voice calls, not just email and data actions?+

Yes. Voice capability is available for collections, back order notifications, and vendor coordination. It adds to integration complexity and investment range. Whether voice is the right channel for your process is assessed during discovery before any recommendation is made.

What if the pilot does not perform as expected?+

We work through issues during the pilot period. If there is a fundamental mismatch between what the process requires and what an agent can reliably deliver, we say so directly. A pilot that ends with an honest answer is a better result than a deployment that fails in production.

What AI agent development services does Tayana provide beyond the initial pilot?+

Expanding agent scope, adding adjacent processes, or building a second coordinating agent are the most common next steps. Ongoing support covers threshold adjustments, rule updates, and integration maintenance as your systems or business rules evolve.

Ready to find out whether your process qualifies?

A 30-minute call is enough to assess fit, confirm integration requirements, and outline a realistic pilot scope.