The interface is visible.The system makes it work.
A customer sees a page, an application, a checkout flow, a recommendation or an answer.
Underneath it may be authentication, inventory, payments, CRM, APIs, business rules, AI models, search, workflow logic, analytics and third-party platforms that were never designed to cooperate.
That is where Pyxl Engineering operates.
We combine product thinking, experience design and technical architecture so the experience a customer touches and the systems underneath it are designed as one product.
Eight families,one engineering practice.
A website can be part of any of these. It is not what defines the practice. The list below is what Pyxl engineers directly, and AI Engineering is substantial enough to have its own section rather than a card the same size as mobile QA.
Custom software and digital products
When the product is specific to the business, the software should be too. Pyxl designs and develops customer-facing products and internal platforms around the workflows, users and systems that make the business distinct.
- Custom software development
- Custom web applications
- SaaS product development
- Enterprise applications
- Customer portals
- Internal applications
- Workflow applications
- Product architecture
- Frontend development
- Backend development
- Responsive applications
- Application modernization
APIs and systems integration
The best digital experience is often constrained by the systems behind it. Pyxl connects the platforms that contain customer data, transactions, operations and business logic so the experience can behave like one product instead of a collection of disconnected tools.
- API development
- REST APIs
- GraphQL where appropriate
- Systems integration
- Third-party integrations
- Microservices
- Service architecture
- Authentication integration
- CRM integration
- Commerce integration
- Inventory integration
- ERP and operational integration
- Payment integration
- Data synchronization
- Webhook architecture
- Connector development
- Middleware and orchestration
AI products frequently need access to the same operational systems as conventional applications. The same integration layer lets an AI assistant or workflow retrieve information and invoke approved tools rather than existing as an isolated chat interface.
Commerce and transaction platforms
Transaction systems become complex long before the customer notices. Catalogs, identity, availability, bids, payments, fees, approvals, notifications, fulfillment and administration all have to agree on what happened. Pyxl engineers the rules underneath the transaction as carefully as the interface around it.
- Marketplace development
- Auction marketplace development
- Commerce architecture
- Headless commerce
- Shopify Plus development
- Custom checkout
- Multi-party payments
- Stripe and payment integration
- Subscription logic
- User accounts
- Seller workflows
- Buyer workflows
- Administrative workflows
- Real-time application logic
- Notifications
- Post-transaction workflows
Mobile application development
Pyxl designs and develops mobile experiences that connect to the same products, APIs and business systems as the rest of the digital ecosystem rather than becoming another isolated channel.
- Mobile product strategy
- iOS and Android experiences
- Cross-platform development
- React Native where appropriate
- API-connected mobile applications
- Authentication
- Push notifications
- Mobile commerce
- Mobile QA
- App deployment support
Modernization without starting over by default
A platform can be strategically important and technically overdue at the same time. Pyxl helps teams understand what should be retained, replaced, decoupled or rebuilt so modernization improves the product without creating unnecessary risk.
- Application architecture
- Technical discovery
- Legacy modernization
- Platform migration
- Replatforming
- Architecture assessment
- Service decomposition
- Microservices
- CMS architecture
- Headless architecture
- Infrastructure planning
- Technical roadmaps
- Technical debt prioritization
Modernization may also mean making existing platforms AI-ready — exposing APIs, structuring data, creating retrieval layers or introducing orchestration services so intelligent experiences can safely use systems that already work.
Built to run
Architecture matters after launch. Pyxl plans deployment, environments, performance and infrastructure around the actual demands of the product so engineering decisions made during the build do not become operational limitations later.
- Cloud architecture
- Hosting architecture
- Environment strategy
- CI/CD
- Containerization
- Docker
- Kubernetes where appropriate
- Caching
- CDN and edge delivery
- Performance optimization
- Version control
- Release management
- Monitoring
- Scalability planning
Accessibility and product assurance
Shipping the feature is only one test of whether a product is ready. Pyxl evaluates applications across accessibility, devices, browsers, workflows and failure states so teams can identify problems before their customers — or their procurement process — do.
- WCAG accessibility audits
- Automated accessibility testing
- Manual accessibility evaluation
- Screen-reader testing
- Mobile-device testing
- Accessibility conformance reports
- Cross-browser QA
- Responsive QA
- Functional testing
- Regression testing
- Pre-launch validation
- Post-remediation verification
Useful AI is rarelyjust a model call.
Production AI products need context, proprietary data, external information, tools, business logic, integrations, evaluation, observability and an experience that gives the model the right job at the right moment.
Pyxl engineers the system around the intelligence — from the user experience and orchestration layer through retrieval, integrations, tools, data and evaluation.
The model is one component. The product is the system around it.
AI products and experiences
- Generative AI applications
- AI assistants
- Conversational products
- AI-powered search
- AI recommendations
- AI decision support
- AI analysis and insight
- Streaming AI experiences
- Structured AI outputs
LLM and model integration
- LLM integration
- OpenAI integration
- Multi-model and model-provider architecture
- Prompt and context architecture
- Structured outputs
- Tool calling
- Function calling
- Model routing where appropriate
- Caching and performance optimization
Pyxl applies and orchestrates models inside useful products. We do not train frontier foundation models, and the strength of the practice is not pretending otherwise.
Retrieval and knowledge
- Retrieval-augmented generation
- First-party knowledge retrieval
- Document retrieval
- Structured data retrieval
- Semantic search
- Knowledge-system architecture
- Context assembly
- Source-aware responses
- Internal knowledge applications
Agents and intelligent workflows
- Agentic workflows
- AI workflow automation
- Tool-using AI systems
- Human-in-the-loop workflows
- Multi-step AI processes
- AI and API orchestration
- Business-system actions
Deliberate automation rather than autonomous-system theater: defined tasks, approved tools, structured workflows, guardrails, logging, and human review where the business requires it.
AI and business systems
- CRM integration
- Commerce integration
- Inventory integration
- Accounting integration
- Operational platform integration
- External data APIs
- First-party data integration
- Reusable connector architecture
Evaluation and observability
- Interaction logging
- Tool-call logging
- AI analytics
- Quality evaluation
- Response evaluation
- Usage analytics
- Failure analysis
- Human review workflows
- AI observability
Six engagements,six different problems.
Chosen because each one proves a different technical muscle rather than repeating the same one. A marketplace where the rules are the product, a production AI platform, a commerce platform that survived an acquisition, an enterprise ecosystem Pyxl inherited and kept running, an application coordinating several systems, and two applications tested for accessibility beyond an automated score.
The stack is technical.The customer experience isn't.
Customers do not care which system owns their profile, which API returns inventory, which model generated the recommendation or which service processes the transaction.
They experience one product. Pyxl engineers the pieces accordingly.
Design, software, AI, integrations, data, commerce and infrastructure are not departments here that hand work to each other. They are layers of the same product, and the seams between them are where products fail.
The systems we have hadto keep alive through a cutover.
Every third-party system named in a delivered engagement, tagged by the motion it serves. Migrations are judged on what kept working, not on what launched.
18 of the 53 run for B2B and eCommerce clients alike, which is why a pattern proven on one client is available to the next.
US-based.Built to flex.
Pyxl combines US-based engineering resources and leadership with vetted nearshore engineers in Mexico and Latin America. We use both deliberately — building the team around the problem rather than forcing every problem into a fixed bench.
Nearshore is not an offshore handoff. It is an extension of the Pyxl engineering team.
We use nearshore resources when an engagement benefits from additional capacity or a specific technical specialty: a migration that needs more throughput, an integration requiring deeper platform experience, a launch window that needs additional engineers, or a capability that would make little sense for a client to hire permanently.
Geography matters. Mexico and Latin America provide meaningful overlap with US working hours, so engineers can participate in the same standups, architecture discussions, reviews and client conversations instead of passing work across an overnight relay.
Pyxl remains accountable for the architecture, quality and result.
One team. Overlapping hours. One standard.
Five reasons,stated plainly.
Product thinking beside the code
The engineer does not receive a design after every consequential decision has already been made. Strategy, UX and architecture develop together.
AI that connects to the business
Pyxl does not treat AI as an isolated chat window. We engineer AI products that can work with proprietary knowledge, external data, APIs, business systems, tools and workflows — with evaluation and observability around the intelligence.
The integrations are part of the experience
A beautiful interface connected badly to CRM, commerce, inventory or operational systems is still a bad product.
Software, not just websites
Pyxl builds transaction systems, marketplaces, AI products, internal applications, APIs, mobile experiences and enterprise integrations in addition to digital websites and experiences.
The team can expand around the problem
US-based and nearshore engineering resources allow Pyxl to add capacity or specialist expertise without replacing the core team or changing the client's operating model.
What buyers askbefore the first call.
Do you build custom software or mostly websites?
Pyxl does both. Our engineering practice includes custom software, web applications, SaaS products, marketplaces, mobile applications, commerce platforms, APIs, enterprise integrations, AI products and platform modernization. A website may be part of the solution. It does not define the practice.
What does AI engineering mean at Pyxl?
AI engineering means designing and building products and workflows in which AI performs a useful role inside a larger software system. That can include LLM integration, AI assistants, retrieval-augmented generation, first-party knowledge systems, agentic workflows, AI-powered search and recommendations, external-data integration, tool calling, business-system integrations, analytics, observability and evaluation. The model is one component of the architecture, not the entire product.
Can you build AI using our private data?
Yes. Depending on the use case, we design retrieval and context architectures that let an AI product use approved first-party documents, structured information and business data rather than reducing the product to a prompt on a public model. The right architecture depends on the data, the security requirements and the workflow, so it is a design decision we make with you rather than a package.
Can you connect AI to our existing systems?
Yes. AI becomes significantly more useful when it can retrieve approved information from, or invoke controlled actions through, the systems the business already uses. The same API and systems-integration capability we use for conventional applications lets us engineer AI alongside CRM, commerce, inventory, operational platforms, first-party databases and external APIs.
Do you build AI agents?
We engineer agentic and tool-using workflows where the problem benefits from them. We prefer deliberate automation over autonomous-system theater: clearly defined tasks, approved tools, structured workflows, guardrails, logging, and human review where the business requires it.
Do you provide US-based engineers?
Yes. Pyxl has US-based engineering resources and leadership, and also works with vetted nearshore engineers in Mexico and Latin America as an extension of the team.
Why do you use nearshore engineers?
Nearshore capacity lets us add throughput or a specialized expertise when a project requires it, without turning the engagement into a disconnected handoff. Mexico and Latin America also overlap meaningfully with US working hours, so the combined team works together in real time rather than across an overnight relay.
Will our project be handed to an outsourced team?
No. Nearshore engineers operate as an extension of the Pyxl team. Pyxl remains responsible for the product direction, architecture, technical standards, quality and delivery.
Can you take over an existing application?
Yes, and not every platform should be rebuilt. We assess an existing application's architecture, technical debt, integrations and business requirements, then determine what should be retained, modernized, decoupled, migrated or replaced. The North American Guitar is seven phases of exactly that, including an acquisition absorbed without a rebuild.
Do you provide ongoing engineering after launch?
Yes. Depending on the engagement we continue supporting platforms through product enhancements, integrations, maintenance, optimization, QA and ongoing engineering.