One Forward Deployed Engineer. Thirteen Specialized AI Agents.

Before any configuration work begins — and continuously afterward — three agents keep the engagement anchored to cost reality instead of scope creep.

• Cost Analysis Agent: Parses vendor contracts, invoices, and usage exports to compare list pricing against actual consumption, surfacing patterns of overspend across CRM, ITSM, and collaboration platforms before recommendations are made.
• User Utilization Agent: Analyzes login frequency, feature-level usage telemetry, and role activity (for example, Salesforce login history, HubSpot seat activity, or ServiceNow fulfiller-versus-requester logs) to identify dormant, underused, or over-provisioned accounts.
• License Optimization Agent: Cross-references utilization findings against actual license tiers and bundles (such as Salesforce Platform versus Sales Cloud, or HubSpot Professional versus Enterprise) to propose a right-sized license mix — every recommendation is flagged for validation against the governing vendor contract before any change is made.

Before a single field or flow is built, two agents establish what the system needs to do and how it should be structured to do it safely.

• Discovery Agent: Runs structured stakeholder interviews, parses existing process documentation, org configuration exports, and historical ticket data to produce a current-state map of how the business actually operates today — not how a slide deck says it operates.
• Architecture Agent: Proposes the target-state data model, integration topology, and sharing/security model, including platform-fit calls (for example, when an Experience Cloud site is the right approved external experience versus a custom-built portal). Every architecture proposal is reviewed and approved by the FDE before build work starts.

Once architecture is approved, three agents handle implementation in parallel, each producing work that traces back to a specific approved requirement.

• Configuration Agent: Implements declarative configuration — objects, fields, flows, permission sets, automation rules — directly against the approved architecture, with every change linked to the requirement it satisfies.
• Integration Agent: Builds and maintains connections between systems (Salesforce to NetSuite, HubSpot to Slack, ServiceNow to a data warehouse, and similar patterns) using a library of reusable connectors rather than one-off, single-use integration code.
• Workflow Agent: Automates multi-step cross-system processes — approval chains, lead routing, case escalation, renewal reminders — removing manual handoffs that otherwise sit on someone's desk.

Moving data and validating a build safely is where traditional projects lose the most time. Three agents compress this phase without skipping steps.

• Migration Agent: Plans and executes data migration — extraction, field mapping, transformation, load, and reconciliation — with dry-run validation passes run before any production cutover.
• Testing Agent: Generates and executes test scripts against configuration and integrations, including regression tests and user-acceptance test scaffolding, so issues surface before production rather than after.
• Documentation Agent: Produces and maintains living documentation — data dictionaries, admin guides, process runbooks, and architecture decision records — kept in sync with what is actually deployed, not written once at kickoff and left to rot.

The engagement doesn't end at go-live. Two agents keep watching the system and keep checking the numbers against reality.

• Monitoring Agent: Watches production systems post-launch for integration failures, workflow errors, license consumption drift, and newly emerging dormant-user patterns — surfacing problems while they're still cheap to fix.
• Savings Verification Agent: Re-measures actual cost and utilization after implementation and license changes go live, comparing results against the original estimate using real invoices and usage data — not assumptions carried over from the proposal.

None of this is full automation replacing human judgment, and PartnerMCP does not position it that way. The agents accelerate analysis, drafting, and repetitive build work at a speed and consistency no manual team can match. But architecture approval, security review, production deployment decisions, and final sign-off on any licensing or configuration change remain with the dedicated Forward Deployed Engineer and PartnerMCP's engineering team.

Every agent output is reviewed against a defined checklist before it reaches your production environment. The FDE is accountable for what ships, why it shipped, and what it costs to run — not the agents, and not a rotating cast of subcontractors billing by the hour.