Routine steps
Classification, extraction, validation, routing, and repair do not always need the most expensive model in the stack.
Product Experience
See how Flev DevOps feels before you send a real failure.
The buyer experience should make the work visible: intake, investigation, evidence, approval, and the reusable runbook all stay connected to the same workflow.
Model Cost And Privacy
Use frontier models only where they matter.
Flev workflows can route routine, structured steps to local or private small models while keeping stronger models available for complex reasoning.
Reviewable routing
Teams should be able to see which model handled which step, why fallback exists, and who can approve changes.
Small-model ready
Better Call evidence shows tool-call accuracy improving from 73.4% to 83.8% on 3,625 granite4.1:3b BFCL v4 cases.
Product Experience
The product surface the buyer should expect
Intake
01
One failing path, not a long requirements document
The team submits a GitHub Actions run, deploy log, Kubernetes namespace, or incident note with the owner and useful result.
- Failure URL
- Repo/service
- Owner
- Success criteria
Studio Review
02
A reviewable investigation tree
Flev shows what was checked, which evidence supports the conclusion, what is still unknown, and which actions need approval.
- Checked logs
- Evidence nodes
- Missing facts
- Approval gate
Deliverable
03
A report the team can use next time
The output is a diagnosis brief, evidence table, runbook patch, approval boundary, and productization recommendation.
- Diagnosis
- Evidence table
- Runbook patch
- Next-run rule
Model Boundary
04
Cost and privacy stay visible
Routine classification, extraction, validation, routing, and repair can use local or private small models while harder reasoning stays on stronger models.
- Local/private route
- Frontier fallback
- Cost review
- Model evidence
What the sprint produces
Workflow from user pain to reusable operations
Submit failure
CI, deploy, Kubernetes, or incident path.
Collect evidence
Logs, diffs, events, run history, and existing runbooks.
Review boundary
Separate read-only investigation from risky actions.
Deliver artifact
Diagnosis, evidence table, runbook, and approval record.
Package pattern
If useful, turn it into a recurring Flev workflow.
Engineering Proof
System architecture behind the experience
Buyers see the workflow. Engineering teams can inspect why the workflow is reviewable, governable, and safer to operate.
Flev
Product workspace: intake, Studio, review tree, sample report, chat/embed, and workflow packaging.
Stable Harness
Runtime control plane: session, evidence, approval, provider, memory, event, and protocol boundaries.
Better Call
Tool-call reliability boundary: validate, normalize, repair when allowed, or block before real tool execution.
Model boundary
Local, private, and frontier models can be routed by task so cost, privacy, and fallback behavior remain reviewable.
Customer environment
The repo, CI, deploy path, Kubernetes context, logs, and existing runbook stay inside the agreed access boundary.
Flev DevOps
Start the intake
Send one failing engineering path. We will scope the smallest useful paid pilot.
Use this checklist before the first call. The goal is not a perfect brief; the goal is enough context to decide whether a 7-day diagnostic sprint can produce a useful result.