{
  "generatedAt": "2026-05-16T00:00:00+05:30",
  "purpose": "Client-ready intake schema for Edxperimental Labs consulting diagnostics and benchmark sprints.",
  "intakeSectionCount": 6,
  "milestoneCount": 4,
  "handoffStageCount": 4,
  "readinessGateCount": 5,
  "deliveryArtifactCount": 4,
  "serviceCatalogCount": 5,
  "contacts": [
    {
      "name": "Sanjay Prasad",
      "email": "sanjay@edxperimentallabs.com",
      "role": "Benchmark design and technical delivery"
    },
    {
      "name": "Saujas",
      "email": "saujas@edxperimentallabs.com",
      "role": "Sales engineering and client solutions"
    }
  ],
  "serviceCatalog": [
    {
      "service": "AI workflow benchmarking",
      "owner": "Sanjay Prasad",
      "buyerQuestion": "Which model, provider, or agent route should handle this workflow?",
      "bestFor": "Teams with one concrete process, examples, and a decision deadline.",
      "startingInputs": [
        "Workflow examples",
        "Expected outputs",
        "Candidate systems",
        "Failure cost"
      ],
      "artifacts": [
        "Task packet",
        "Run table",
        "Trace ledger",
        "Decision memo"
      ],
      "readiness": 82,
      "nextAction": "Send one workflow and two candidate routes for a diagnostic scope."
    },
    {
      "service": "Agent reliability review",
      "owner": "Sanjay Prasad",
      "buyerQuestion": "Can this agent complete work safely across tools, browser state, and handoff boundaries?",
      "bestFor": "Teams piloting coding agents, browser agents, support agents, or internal automation.",
      "startingInputs": [
        "Agent trace",
        "Tool permissions",
        "Success criteria",
        "Human handoff rule"
      ],
      "artifacts": [
        "Reliability scorecard",
        "Failure taxonomy",
        "Tool-risk map",
        "Release gate"
      ],
      "readiness": 78,
      "nextAction": "Share a current agent demo, transcript, or run log for trace review."
    },
    {
      "service": "Model and provider selection",
      "owner": "Sanjay Prasad",
      "buyerQuestion": "What should run on frontier APIs, faster hosted models, open-weight inference, or human review?",
      "bestFor": "Teams balancing quality, latency, cost, data boundary, and vendor risk.",
      "startingInputs": [
        "Monthly volume",
        "Latency target",
        "Privacy boundary",
        "Provider shortlist"
      ],
      "artifacts": [
        "Route matrix",
        "Cost curve",
        "Fallback policy",
        "Procurement memo"
      ],
      "readiness": 80,
      "nextAction": "Send workload volume, context length, output length, and candidate vendors."
    },
    {
      "service": "AI security and risk sprint",
      "owner": "Sanjay Prasad and Saujas",
      "buyerQuestion": "Where can prompt injection, excessive agency, data exposure, or weak escalation break the workflow?",
      "bestFor": "Teams moving from demo to production with tool access, customer data, or policy-sensitive outputs.",
      "startingInputs": [
        "Threat model",
        "Tool scope",
        "Sensitive fields",
        "Incident examples"
      ],
      "artifacts": [
        "Security task pack",
        "Risk register",
        "Control deck",
        "Launch blockers"
      ],
      "readiness": 74,
      "nextAction": "Share the riskiest tool/action path and the data the agent should never reveal."
    },
    {
      "service": "Sales-engineering diagnostic",
      "owner": "Saujas",
      "buyerQuestion": "What is the smallest sprint that would answer the buyer's AI decision?",
      "bestFor": "Founders or operators who need a scoped benchmark before a larger AI build.",
      "startingInputs": [
        "Business goal",
        "Stakeholder map",
        "Current workflow",
        "Budget signal"
      ],
      "artifacts": [
        "Discovery memo",
        "Sprint scope",
        "Access checklist",
        "Proposal outline"
      ],
      "readiness": 86,
      "nextAction": "Send a short buyer problem statement and target decision date."
    }
  ],
  "salesEngineeringHandoff": [
    {
      "stage": "Lead qualification",
      "owner": "Saujas",
      "artifact": "Discovery note",
      "evidence": "Workflow, buyer decision, urgency, data sensitivity, budget signal, and stakeholder map."
    },
    {
      "stage": "Technical scoping",
      "owner": "Sanjay Prasad",
      "artifact": "Benchmark scope",
      "evidence": "Task families, candidate systems, scoring rubric, holdout plan, and replay requirements."
    },
    {
      "stage": "Sprint proposal",
      "owner": "Saujas",
      "artifact": "Proposal memo",
      "evidence": "Timeline, deliverables, access requirements, commercial assumptions, and acceptance gates."
    },
    {
      "stage": "Delivery review",
      "owner": "Sanjay Prasad and Saujas",
      "artifact": "Decision packet",
      "evidence": "Run table, trace links, risk register, deployment recommendation, and next sprint."
    }
  ],
  "engagementReadinessGates": [
    {
      "gate": "Workflow specificity",
      "proof": "One workflow with owner, inputs, outputs, volume, and failure cost."
    },
    {
      "gate": "Evidence access",
      "proof": "Representative prompts, documents, tickets, traces, screenshots, or policies are available."
    },
    {
      "gate": "Decision deadline",
      "proof": "The buyer knows whether the sprint must answer buy, build, switch, ship, pause, or redesign."
    },
    {
      "gate": "Candidate systems",
      "proof": "At least two model/provider/agent routes and one baseline process are named."
    },
    {
      "gate": "Review owner",
      "proof": "A human reviewer can judge correctness, partial credit, and unacceptable failures."
    }
  ],
  "deliveryArtifacts": [
    {
      "title": "Workflow risk map",
      "purpose": "Shows where the current process fails, what AI could improve, and what should remain human-reviewed."
    },
    {
      "title": "Benchmark task packet",
      "purpose": "Defines inputs, expected outputs, rubrics, holdouts, and evidence requirements before any model runs."
    },
    {
      "title": "Run and trace ledger",
      "purpose": "Captures model ids, prompts, artifacts, latency, cost, reviewer notes, and failure classes."
    },
    {
      "title": "Deployment decision memo",
      "purpose": "Turns evidence into a recommendation, fallback route, monitoring plan, and next-sprint backlog."
    }
  ],
  "files": [
    {
      "title": "Benchmark Intake Template",
      "href": "/reports/consulting/benchmark-intake-template.md",
      "kind": "markdown",
      "description": "Buyer-facing worksheet for workflow, evidence, constraints, candidates, and acceptance gates."
    },
    {
      "title": "Consulting Sprint Proposal",
      "href": "/reports/consulting/consulting-sprint-proposal.md",
      "kind": "markdown",
      "description": "Reusable proposal outline for diagnostic, benchmark, and deployment-review sprints."
    },
    {
      "title": "Consulting Intake Schema",
      "href": "/reports/consulting/consulting-intake-schema.json",
      "kind": "json",
      "description": "Structured client-ready intake schema for future CRM/provider integration."
    },
    {
      "title": "Consulting Operating Plan",
      "href": "/reports/consulting/consulting-operating-plan.md",
      "kind": "markdown",
      "description": "Sales-engineering handoff, readiness gates, delivery artifacts, and owner routing."
    },
    {
      "title": "Consulting Service Catalog",
      "href": "/reports/consulting/service-catalog.md",
      "kind": "markdown",
      "description": "Buyer-facing service catalog with owners, readiness, inputs, artifacts, and next actions."
    },
    {
      "title": "Consulting Service Catalog JSON",
      "href": "/reports/consulting/service-catalog.json",
      "kind": "json",
      "description": "Structured service catalog for future CRM, proposal, or Studio integration."
    }
  ]
}