Golden-path demos on demand
Record a golden-path demo once and let an agent replay it on demand, live on a real device, for prospects or docs.
Three pains every sales and BD team hits weekly. Each one is what your reps actually complain about, not what a feature page would call them.
Product demos, onboarding walkthroughs, and mobile regression suites all burn human hours on the same scripted paths, release after release.
Every pipeline below is a shape you wire on the canvas using the crew and tools further down. Not a feature we ship for you, a pattern you configure.
Record a golden-path demo once and let an agent replay it on demand, live on a real device, for prospects or docs.
QA agencies run regression suites across client apps in parallel, on physical phones.
Recordings and pass/fail reports per run. Same coverage, a fraction of the hours.
Real personas from the tech_team crew. Each ships with a tuned system prompt and a default tool allowlist. Swap models per persona on the canvas.
Owns the golden paths and signs off the pass/fail criteria.
Walks each client app screen by screen on real hardware.
Schedules parallel suites and ships the per-run reports.
Keeps demo runs presentable and flags visual regressions.
Every tool below is a real shared tool from the Melaya bundle. Allowlist per agent; HITL-gate the writes; revoke any of them in one click.
Replays demos and regression paths on physical phones, step by step.
Files failures and reports where the team already works.
Turns runs into client-ready reports.
Reads specs and logs alongside the device runs.
Every pipeline ships with three layers of knowledge access. Mix and match per agent on the canvas. No shared vector space with another tenant, no surprise reads, no opaque retrieval.
includeContextPer-pipeline documents appended to specific agents' input on every run. The ICP brief, playbook, pricing sheet, or won-deal email corpus. Whatever needs to be there before the agent thinks. You pick which personas get which docs.
rag_retrieveA scoped tool granted per-agent. When the agent decides it needs more depth, it queries the workflow's vector store on demand. Same knowledge base as Static context, accessed only when the model asks for it.
pipeline_memoryPipeline-level state that carries from one run to the next. Yesterday's research is in scope for today's follow-up. The crew remembers what it already prospected, what got approved, what was sent. The audit log is the second-order knowledge base.
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