A 4-week fixed-scope engagement to move from abstract ambition to a deployable, sovereign roadmap. We validate the business case, design the agent workforce, and plan the infrastructure before writing a single line of code.
Teams start with code, not architecture. They chase impressive demos without defining the business case or understanding infrastructure constraints. Six months later, the pilot is still "almost ready."
Start with P&L impact, decompose into agent-achievable tasks, filter for suitability, then design. Every agent has a job description, success metrics, and a clear path to production before development begins.
A signed-off executive document that defines exactly what to build, where to run it, and the ROI it will deliver. This serves as the "Green Light" document for your internal stakeholders.
Outcome decomposition showing how agent tasks connect to P&L drivers.
Agent Job Descriptions for each prioritized agent—role, boundaries, tools, fallbacks.
Loom deployment plan—target environment, MCP connections, Sentinel guardrails.
We filter use cases to find the "Goldilocks Zone"—high value, manageable risk.
Decisions requiring moral judgment or where consequence of error is severe.
e.g., Medical diagnosis, Diplomatic negotiationAgent drafts and advises. Human makes final decision with full accountability.
e.g., Loan application processing, Legal reviewClear rules, basic automation. No need for AI reasoning.
e.g., Data entry, Simple routingMulti-step reasoning, clear success criteria, bounded risk. Agents excel here.
e.g., Invoice processing, IT triage, Customer serviceIf clear rules and basic automation deliver the outcome, we don't build agents. We protect your ROI by killing bad ideas early.
From abstract ambition to deployable roadmap.
Interview executive stakeholders to identify P&L drivers (e.g., "Reduce OPEX by 10%") and map them to specific, repeatable agent tasks.
Identify "Data Gravity" constraints. Map where your core data lives (Mainframe, SQL, ERP) and flag PII/PHI that cannot leave your VPC.
Eliminate "Low Complexity/Low Risk" tasks (better suited for RPA) and "High Risk/High Complexity" tasks (better suited for humans).
Formally reject opportunities that rely on undocumented "tribal knowledge" or lack clear success metrics. Protect ROI before you spend it.
Define the agent's title, reporting structure, and triggers (Reactive vs. Proactive vs. Ambient).
Map inputs/outputs, set "Sovereign Boundaries" (e.g., "Cannot finalize denial >$50k without approval"), list required MCP connections.
Map the agent's graduation path: Shadow Mode (Pilot) → Supervised Mode (Production) → Full Autonomy (Scale).
Diagram the deployment target (AWS/Azure/On-Prem), MCP connections to legacy systems, and guardrails at the Loom Sentinel layer.
We treat agents like new hires. A clear charter, defined triggers, and agreed levels of human oversight.
Goal: Reduce processing time for loan applications
30% reduction in manual exception handling time
Notify loan officer via workflow system for manual intervention
Every prioritized agent gets a complete Job Description—ready to drive architecture decisions and Weaver development.
The engagement output leads directly to execution.
The deliverable from this engagement. Signed off by your stakeholders as the "Green Light" document.
Installation of the sovereign runtime engine on your infrastructure.
Marketplace Deployment (for standard agents) or Weaver Build (for custom agents designed in Week 3).
30-minute discovery call. We'll discuss your AI ambitions, assess fit, and outline how Architect the Outcome could work for your organization.
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