Models and inference
Hosted or self-managed options, task fit, context, structured output, tool use, latency, cost, safety, fallback, and provider portability.
Technology
Choose technology by operating requirements, not by logo count
Kubto evaluates model, retrieval, data, runtime, integration, frontend, cloud, and observability choices against the use case, constraints, team skills, and exit options.
Who this is for
Architects, engineering leaders, product teams, and technical buyers comparing how a proposed stack will behave, integrate, scale, and remain supportable.
Problem to solve
Fast-moving AI and cloud ecosystems make it easy to assemble a demo and difficult to understand lock-in, failure behavior, evaluation, security, cost, and ownership.
Scope
Technology decisions Kubto can help structure
Retrieval and data
Relational, vector, search, object, cache, streaming, and queue systems selected around access, consistency, scale, recovery, and operations.
Application runtimes
Python, Node, PHP, and frontend or API patterns chosen around the current platform, workload, deployment standards, and team ownership.
Orchestration and agents
Deterministic workflows, model-assisted steps, tool permissions, state, retries, approval, audit, and exception handling.
Commerce and content platforms
Magento, Adobe Commerce, Shopify, WooCommerce, WordPress, headless, and custom integration boundaries.
Cloud and operations
Compute, containers, networking, deployment, secrets, observability, resilience, performance, and cost management.
Architecture
A decision process that leaves an audit trail
- 01
Requirements
Translate the user workflow into quality, latency, availability, privacy, integration, cost, and ownership requirements.
- 02
Options
Compare plausible patterns using explicit criteria, dependencies, risks, maturity, and switching cost.
- 03
Validation
Use a focused spike, evaluation set, load profile, or failure test to resolve the highest-risk assumptions.
- 04
Decision and review
Record the choice, rejected options, consequences, controls, owner, and trigger for revisiting it.
Deliverables
What the engagement can produce
✓
Architecture decision records
Concise records of context, options, decision, tradeoffs, dependencies, and review triggers.
✓
Reference architecture
Components, interfaces, data flow, trust boundaries, operational signals, and deployment relationships.
✓
Technical validation
A bounded prototype or evaluation that tests the uncertain quality, integration, performance, or operating assumption.
✓
Lifecycle plan
Versioning, testing, monitoring, provider changes, deprecation, portability, and ownership expectations.
Boundaries
Boundaries and decisions to verify
Good work is easier to trust when the team knows what is included, what still needs proof, and who owns each decision.
Technology changes
Provider capabilities, pricing, limits, and terms change. Current details are verified during the engagement rather than implied by this page.
Model outputs remain probabilistic
Guardrails and evaluation reduce risk but do not make generated output universally correct or appropriate for unsupervised high-impact decisions.
Compatibility is environment-specific
Versions, extensions, data models, network policy, contracts, and existing standards determine integration feasibility.
Turn a disputed stack choice into a testable decision
Share the use case, current standards, options under consideration, and the risk the team needs to resolve.
Discuss the architecture decision