AI and application integrations.
Connect applications and integrate suitable AI capabilities through defined, validated interfaces.
INTEGRATIONS & AUTOMATION / CONNECTED SOFTWARE
Connected software.
Fewer handoffs.
AI Integration, application connections, and workflow automation for production systems. Combine model capabilities with validated interfaces, explicit business rules, and operational visibility.
Discuss your projectWHAT WE CAN BUILD TOGETHER
Workflow automation.
Combine generative and interpretive tasks with deterministic content and operational processes.
Observable data movement.
Keep API and data pipeline failures understandable with logging, validation, and recovery paths.
Every handoff.
Accounted for.
Automation needs more than a successful happy path. We consider the source data, destination constraints, and what happens when a step cannot complete.
Explore case studiesAI INTEGRATION / PRODUCTION SYSTEMS
Model capabilities.
Inside your application.
Integrate AI into existing products, custom software, WordPress, and API-driven systems. Define the task, the input boundary, and how the application accepts the result.
Prepare usable outputs.
Content generation and structured outputs can support editorial pipelines and AI-enabled product features. Validate the expected format and review content before its next step.
Work with supplied context.
Classification, summarization, data transformation, and workflow decision support can assist internal and operational workflows within explicit acceptance rules.
Bound the actions.
Agentic workflows and tool-using AI systems need defined tools, permission checks, constrained actions, and human review wherever the workflow requires approval.
PROVIDER-AGNOSTIC AI
Keep the provider
behind a boundary.
We work with major providers including OpenAI, Anthropic, and Google. An AI service abstraction separates application behavior from provider-specific requests, model selection, and responses.
This keeps application architecture clear, reduces unnecessary lock-in, and makes provider changes easier to manage. Select models for the use case rather than binding every feature permanently to one model.
Providers differ in output formats, tools, limits, and model behavior. A provider change still requires capability checks, output validation, and testing against the application's acceptance criteria. Interchangeability is a design goal with a validation step.
01 / APPLICATIONProduct behavior & business workflow
02 / AI SERVICE / ABSTRACTIONDefined capabilities & provider-specific adapters
03 / PROVIDER / MODELOpenAI · Anthropic · Google
AI + DETERMINISTIC AUTOMATION
Interpret with AI.
Control with software.
AI handles generative and interpretive tasks. Deterministic application logic owns validation, state, permissions, business rules, scheduling, integration boundaries, and acceptance.
Validate model output before changing application state. Expose only permitted tools, handle failed or unacceptable results, and keep the workflow traceable through its application logic.
Human control at defined steps.
Agree requirements and allowed inputs before implementation. Test expected and failed outputs, define what needs human review, and keep acceptance and release decisions with responsible engineers and operators. Review can mean approving a draft or confirming a proposed action before the application executes it.
IMPLEMENTED IN WORDPRESS
A product.
A defined AI boundary.
ExMoment Author connects editorial work to the WordPress AI Client. Its Library, Jobs, and Settings modules demonstrate how model requests fit into a configured application workflow. The product and engineering case study show that boundary in context.
CONNECTED DISCIPLINES
Part of a wider system.
LET’S BUILD SOMETHING THAT HOLDS UP.
Your next system. Our engineering.
Tell us what you’re building, improving, or trying to connect.