AI Agent Development
AI agents that complete work, not just answer questions
We build agents that can call APIs, follow procedures and escalate when confidence is low — designed as software systems, not unbounded chatbots.
Definition. An AI agent is software that uses a language model to decide which tools to call, in what order, to complete a goal. In a business setting that means constrained tools, audit logs, permissions and a human path for exceptions.
An agent without constraints is a liability
Agents fail when they can take too many actions, cannot see the right systems, or have no definition of done. The product problem is control, not personality.
Unbounded tool access
If an agent can update any record, a single bad decision becomes an operational incident.
No procedure
Without a defined playbook, agents improvise. That is fine for drafts, not for refunds, orders or customer data.
Invisible failures
If you cannot inspect traces, you cannot improve the agent or explain what it did.
Capabilities
What we build
Specific delivery, not a vague capability list.
Operations agents
Agents that prepare tickets, classify issues, draft actions and wait for approval on sensitive steps.
Product agents
In-app agents that help users complete a job using your product’s own APIs.
Evaluation harnesses
Scenario sets that tell you whether the agent is getting better before you widen its permissions.
Solutions
Common implementation scenarios
Support operations
Retrieve policy, draft responses, propose macros and only execute account changes with approval.
Ecommerce operations
Investigate order issues, prepare catalog updates and coordinate across Shopify and internal tools.
Internal research and routing
Gather context from multiple systems and produce a recommended next step for a human operator.
How we work
Development process
01
Discovery
We clarify the business problem, current systems, constraints, success metrics and decision-makers before recommending a build.
02
Strategy
We define the product scope, delivery sequence and commercial trade-offs so engineering work maps to a measurable outcome.
03
Architecture
We design the application, data, integration and security model before implementation starts, reducing rework later.
04
UI/UX
We design the interfaces operators and customers will actually use — with clarity, accessibility and conversion in mind.
05
Development
We implement in short, reviewable increments with staging environments and visible progress against the agreed scope.
06
QA
We test functional flows, edge cases, integrations, performance and release readiness before anything reaches production.
07
Launch
We ship with a controlled cutover, monitoring and a clear rollback plan so go-live is an operational event, not a gamble.
08
Support & Optimization
After launch we stabilize, measure and improve — fixing issues quickly and iterating on the features that affect the business.
Stack
Technologies
- AI agents
- OpenAI
- LLMs
- AI APIs
- Node.js
- TypeScript
Industries
Where this service is typically used
Ecommerce
We help ecommerce businesses build Shopify experiences, operational AI, mobile clients and the integrations that keep catalog, orders and inventory honest.
SaaS
We help software companies ship AI capabilities, integration surfaces and mobile clients that respect tenancy, metering and a roadmap you can maintain.
Retail
We help retailers connect commerce, operations apps and back-office systems so availability, orders and exceptions are not a manual sport.
Engagement
How we work commercially
Fixed scope
A defined outcome, timeline and budget after discovery. Best when requirements are clear enough to estimate with confidence.
Dedicated team
A stable product squad that works as an extension of your team across a roadmap, not a one-off ticket list.
Ongoing development
Retained engineering capacity for iteration, integrations, maintenance and new capabilities after the first release.
Consulting
Architecture, vendor selection, AI feasibility, Shopify Plus planning or integration design without a full build engagement.
FAQ
Questions about ai agent development
It is software that can choose tools and complete a multi-step job under rules you define. It is not an unsupervised employee.
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How AI agents work in a business product
A practical explanation of AI agents: tools, planning, guardrails, evaluation and when a chatbot is the wrong interface. Written for product and operations leaders.
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What actually drives AI application cost: data access, evaluation, guardrails, integrations and whether you are adding a feature or building a product.
Learn moreNext step
Scope an AI agent workflow
Describe the job the agent should complete and the systems it would need. We will propose a constrained first version.