AI Integration Services
Add AI to the product you already operate
We connect language models, retrieval and automations to existing applications so teams get a useful capability without waiting for a full rebuild.
Definition. AI integration is the process of connecting models and supporting infrastructure to software you already run — including identity, data, permissions, logging and the user interface that exposes the new capability.
Buying an AI tool is not the same as making it work inside your stack
Standalone AI products often cannot see your catalog, tickets, orders or customer context. Integration is the work that makes the capability useful.
Disconnected tools
Staff copy context into a separate chatbot, then copy answers back. The workflow never actually changed.
Unsafe data exposure
Connecting a model without a permission model can leak customer or commercial data into the wrong place.
No owner in the product
If the feature has no place in the existing UX, people will not use it — even if the model quality is fine.
Capabilities
What we build
Specific delivery, not a vague capability list.
In-product AI features
Assist, generate, classify and summarize inside the applications your team already lives in.
Retrieval over business data
Answers grounded in product catalogs, policies, tickets and internal documentation.
Workflow automations
AI steps inside existing operational pipelines, with retries and human review.
Solutions
Common implementation scenarios
SaaS product AI
Add generation or assistance to a multi-tenant product with usage controls and tenant isolation.
Ecommerce operations AI
Support deflection, catalog enrichment and merchandising assistance connected to Shopify data.
Internal systems
Give operations teams AI inside CRM, ERP-adjacent workflows or custom admin tools.
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
- OpenAI
- LLMs
- AI APIs
- Vector databases
- 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 integration
Yes. That is the most common AI engagement: identify one workflow, connect the required data, and ship a production feature with monitoring.
Related services
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Connect large language models to your product, data and permissions model with evaluation and cost controls.
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Build and customize Shopify stores, apps, themes and Shopify Plus solutions around merchandising and operations.
Learn moreRelated reading
Shopify
How to integrate AI into Shopify without a storefront gimmick
Where AI actually helps Shopify merchants — Admin, catalog, support and ops — and how to connect models to Shopify APIs with review and permissions.
Learn moreAI
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.
Learn moreNext step
Plan an AI integration
Tell us which product or workflow should get AI first. We will map data access, risk and a realistic first release.