01
Start with the operating problem
Define the user, workflow, current failure, exception path, business measure, and accountable owner.
Solutions by product, workflow, platform, and operating layer
Choose the smallest solution that can prove useful value
Kubto connects AI, configurable product capabilities, commerce engineering, and infrastructure without pretending every problem needs the same model or platform.
Each implementation begins with source data, users, permissions, technical constraints, a measurable baseline, risk, and named production ownership. Claims and component choices follow evidence from that environment.
02
Evaluate the real estate
Use representative data, exact platform versions, integrations, permissions, topology, team constraints, and support model.
03
Make evidence a release gate
Combine quality, security, workflow, operational, and business evaluation before production adoption.
Configurable products
Product capabilities delivered with scoped implementation
Kubto configures the product capability around the client’s data, experience, platform, controls, deployment, evaluation, and operating model. Hosting, support, and licensing are confirmed in the engagement.
Kubto Search
Hybrid lexical and semantic retrieval, facets, ranking controls, analytics, evaluation, and relevance operations.
Review architecture and boundariesRecommendation Engine
Catalog and behavioral candidates, merchandising controls, placement contracts, fallbacks, experimentation, and privacy boundaries.
Review architecture and boundariesKubto Render
Crawler-ready HTML for approved JavaScript routes with parity, cache, invalidation, diagnostics, fallback, and migration boundaries.
Review architecture and boundariesAI and data systems
AI architecture tied to evidence, permissions, and workflow ownership
Start with a real decision or workflow. Kubto separates deterministic logic, retrieval, model judgment, tool actions, human review, and production operations before selecting components.
Enterprise AI engineering
Governed agents, model workflows, tool integration, evaluations, deployment, risk controls, and operational handoff.
Review architecture and boundariesRAG knowledge assistants
ACL-aware ingestion, hybrid retrieval, citations, answer policy, prompt-injection boundaries, and human escalation.
Review architecture and boundariesVector and hybrid retrieval
Embeddings, metadata, ANN indexes, lexical-vector fusion, reranking, evaluation, tenancy, and index operations.
Review architecture and boundariesSemantic discovery
A governed product-meaning layer across search, browse, taxonomy, recommendations, assistants, and journey measurement.
Review architecture and boundariesCommerce platforms
Platform-specific engineering rather than generic AI overlays
Catalog models, account rules, APIs, extension points, queues, storefronts, release processes, and operational ownership differ by platform. Each page documents those boundaries.
Magento 2 engineering
EAV, modules, indexers, MSI, APIs, queues, storefronts, performance, deployment, security, and operations.
Review architecture and boundariesAdobe Commerce engineering
Cloud delivery, Fastly, B2B, Adobe services, integrations, storefronts, observability, and enterprise governance.
Review architecture and boundariesMagento AI Search
Magento-specific catalog mapping, update lifecycle, commerce eligibility, hybrid retrieval, facets, storefront integration, and evaluation.
Review architecture and boundariesAdobe Commerce AI Search
Enterprise catalog and B2B boundaries, data services, storefront APIs, merchandising, cloud release, and search quality.
Review architecture and boundariesShopify engineering
Admin and Storefront APIs, webhooks, apps, themes, Hydrogen, Functions, integrations, discovery, and automation.
Review architecture and boundariesWordPress & WooCommerce
Plugins, themes, content and product data, APIs, scheduled work, cache, security, search, assistants, and technical SEO.
Review architecture and boundariesInfrastructure and assurance
Production foundations around every application
AI and commerce systems still depend on identity, networking, compute, storage, databases, delivery pipelines, observability, resilience, backup, security, cost control, and supported ownership.
Cloud, server, and DevOps infrastructure
Architecture, deployment, containers, CI/CD, networking, observability, resilience, backup, security, cost, and operations.
Review architecture and boundariesTechnology architecture
How Kubto evaluates models, retrieval systems, runtimes, data stores, cloud services, containers, integrations, and operating tradeoffs.
Review architecture and boundariesSecurity and AI risk
Identity, least privilege, secrets, data boundaries, model risk, prompt injection, supply chain, logging, incident response, and ownership.
Review architecture and boundariesAI infrastructure readiness guide
A practical review of topology, identity, networking, data, observability, resilience, cost, and production ownership.
Review architecture and boundariesNot sure where the boundary should sit?
Share the workflow, data, platform, risk, and operating constraints. Kubto can help separate the product, custom engineering, infrastructure, and ownership decisions before you commit to a build.
Discuss a solution assessment