Custom web
Purpose-built responsive interfaces where performance, conversion and product behavior matter.
WordPress
Custom-coded WordPress experiences for editable marketing, publishing, SEO/GEO and integrated business sites.
Mobile apps
Cross-platform mobile experiences where camera, notifications, account state and field usage matter.
Node / TypeScript
Business APIs, integrations, workflows and application services.
Python / FastAPI
AI services, computer vision, processing pipelines and specialized backend workloads.
REST & webhooks
Reliable integration between systems and event-driven workflows.
Server-side functions
Focused processing, secure API calls and backend automation close to the product.
Relational data
Users, roles, workflow state, transactions, audit history and structured records.
Application ORM
Typed data access patterns such as Prisma when they fit the product architecture.
Retrieval / knowledge
Chunking, embeddings, vector retrieval and source-aware knowledge access where RAG is appropriate.
LLM workflows
Summarization, classification, extraction, drafting, reasoning and structured output.
RAG systems
Ground AI in approved company knowledge and operational context.
Document intelligence
Read, classify, extract, validate and route PDFs, forms, email and uploads.
Computer vision
Surface detection, image understanding, masks and visual workflows.
Generative imaging
Controlled image transformation where scene preservation and user intent must be constrained.
Agent orchestration
Permissioned tools, bounded action loops, evidence, escalation and auditability.
Human review
Review gates, exception queues and explicit responsibility for high-impact work.
Provider flexibility
Architecture should avoid unnecessary model lock-in when the workflow benefits from provider choice.
Vercel-style deployment
Fast web deployment, previews and environment separation for suitable front-end applications.
Secure environment variables
Secrets and API keys stay server-side and outside public browser code.
Caching & CDN
Use caching intentionally for public content and expensive repeatable responses.
Observability
Errors, latency, model usage, failures and operational exceptions need visibility after launch.
Inbound parsing, routing, drafts, notifications and thread context.
CRM
Customers, opportunities, tasks, activities and ownership.
Google / Microsoft workspace
Documents, calendars, email and collaboration where authorized integrations exist.
Payments & commerce
Checkout, invoices, order state and commercial workflows when the product requires them.
Storage
Documents, media, generated assets and versioned evidence.
External APIs
Verification, logistics, data providers, specialist services and partner systems.
Messaging
Internal chat, mentions, notifications, summaries and action context.
Legacy systems
Custom adapters and staged migration where a full replacement is not sensible.
Prefer boring foundations
Use proven databases, auth and state patterns so innovation stays focused on the differentiating layer.
Prototype uncertainty
Use experimentation for the uncertain AI or UX behavior, not for basic engineering that already has known patterns.
Keep data ownership clear
Know where truth lives before adding automation and AI around it.
Do not expose secrets
Browser convenience is never a reason to expose private API credentials.
Design for replacement
Providers and models change. Keep interfaces modular where the economics justify flexibility.
Optimize after observing
Measure actual latency, usage and cost before premature optimization.
Need the stack chosen around your operation?
Use the Project Planner or Architecture Library. The right technology should be an outcome of the system design.
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