Proof artifacts
Proof should be inspectable, not invented.
Devlyn does not need fake case studies to explain the model. The paid trial should create artifacts a buyer can inspect inside their actual workflow.
What counts as proof?
Pull requests, eval reports, workflow maps, decision records, security findings, metric snapshots, and role-specific notes tied to the buyer’s real codebase or data environment.
AI feature shipped
A real product slice reaches users behind a flag, with the PRs, states, and telemetry to inspect it.
RAG quality improved
Retrieval moves from confident-but-wrong to grounded and cited, measured against a relevance baseline.
Platform reliability or cost visibility
Model access, traces, and spend become consistent and visible instead of scattered per team.
Agent workflow controlled
A multi-step workflow gains tool permissions, approval gates, retries, and traces you can audit.
Security risks identified
AI-specific risks — injection, leakage, unsafe tool authority — are found, tested, and ranked for fix.
Product or data decision clarified
A messy question becomes a defensible decision memo backed by a metric tree and baseline analysis.
Artifact gallery
Representative proof from a trial.
These are artifact types, not fabricated client outcomes.
Pull request card
The trial should create inspectable code, not a private demo.
Eval report
Quality, retrieval, routing, or workflow behavior should have a baseline.
Architecture decision record
Tradeoffs should be written clearly enough for your team to maintain.
Workflow map
The engineer should make scope, actors, systems, and failure paths visible.
Security finding
A concrete AI risk with severity, reproduction, and remediation path.
Metric snapshot
A baseline that clarifies whether a product or model change moved the decision metric.
Bench proof
Use proof carefully.
When logos or enterprise references appear, they should be framed as Viitor Cloud delivery-bench context unless a direct Devlyn client relationship is verified. This keeps the trust story useful without overstating it.
FAQ
Proof questions.
Does Devlyn publish named case studies?
This page does not invent named client case studies. It focuses on representative artifacts a trial should produce.
What should we inspect during a trial?
Pull requests, eval reports, architecture notes, workflow maps, security findings, and decision memos tied to the role.
Can proof be anonymized?
Yes. Buyer-sensitive work can be summarized as anonymized engagement patterns or representative artifacts.
Why not show fake metrics?
Fake metrics reduce trust. Devlyn should show what a buyer can inspect, not made-up outcomes.
Can we request references?
Raise proof and reference needs during the role scope so Devlyn can explain what is available and what cannot be disclosed.
How does this connect to pricing?
The trial exists so the buyer can judge fit before continuing month-to-month.