Rivac AI LabsAgentic Search Optimizer
AI browsing agents don't just read pages anymore (they try to complete tasks on them: check a price, book a slot, submit a form) and a site built only for human eyes often can't be operated by an agent at all. This service optimizes a site for agentic use through WebMCP and related protocols, structuring key actions so AI agents can reliably parse, navigate, and complete tasks on the client's behalf. It's for brands whose customers increasingly delegate research and transactions to AI assistants, and who don't want to be invisible or unusable the moment that happens. The result is a site AI agents can actually act on, not just read about.
This is a capability we deliver for you as a service, not a role we’re hiring for.
How We’d Approach This
A clear, staged plan, not a black box
These are the service-specific steps inside our six-step process.
- 1
Test the site's key user journeys (search, compare, checkout, booking) with real AI agents to find exactly where they fail or get stuck.
- 2
Implement WebMCP or equivalent agentic-interaction support for one high-value task and re-test with the same agents.
- 3
Confirm the task now completes reliably and review the fix with you before extending it further.
- 4
Roll agentic-task support out across remaining key journeys and monitor agent-completion success as browsing agents evolve.
What You Get
Deliverables from this engagement
- A WebMCP or agentic-interaction implementation for key site actions
- An agent-task-completion test report showing before/after results
- Documentation of supported agentic actions for your dev team
- Ongoing monitoring as agent protocols and behavior evolve
Six Ways We Could Architect This
Different engagement, different build, pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Read all 6 architectures as text
Lean Fast-Start Architecture
Audit
- Key User Tasks Identified
- Current Page Structure Reviewed
- Agent Readability Gaps Found
Build
- Basic WebMCP Endpoint Defined
- Action Schema For Key Task
- Structured Response Format Added
Validation
- Manual Agent Simulation Test
- Task Completion Verified
Delivery
- Deployed To Production
- Client Walkthrough
- Task Success Confirmation
- Next Task Backlog Created
Cloud-Native / Managed Services Architecture
Source Layer
- Client Site Application Layer
- Managed API Gateway
- WebMCP Server Hosting
Agentic Operations
- Managed Action Schema Registry
- Structured Response Formatter Service
- Session State Store
Validation Layer
- Agent Simulation Testing Service
- Task Success Analytics
Delivery
- Client Facing Agent Readiness Dashboard
- Automated Uptime Monitoring
- Version Rollout Pipeline
- Usage Analytics Export
Event-Driven & Automation-First Architecture
Triggers
- New Product Or Page Added
- Automated Action Schema Scan
- Agent Task Failure Detected
- Auto Diagnostic Job Triggered
Automation Layer
- Auto Generated WebMCP Action
- Auto Validated Response Schema
- Auto Deployed To Staging Agent Endpoint
Review Gate
- Simulated Agent Task Succeeds
- Flag Failure To Engineer
- Auto Promoted To Production
Delivery
- Deployment Notification Sent
- Scheduled Agent Success Rate Report
- Task Coverage Backlog Updated
Enterprise-Grade & Compliance-Ready Architecture
Governance Layer
- Agent Access Policy
- Approved Agent Actions List
- Transaction Authorization Rules
Secure Deployment
- Access Controlled WebMCP Config
- Role Based Change Approval
- Versioned Action Schema History
Auditable Process
- Security Review Of Each Action
- Cross Team Sign Off
- Transaction Audit Log
Compliance Delivery
- Audit Trail Export
- Redundant Config Backup
- Signed Off Agentic Setup
- Quarterly Action Review
AI-Augmented, Human-in-the-Loop Architecture
Data Ingestion
- Site Task And Workflow Map
- Target Agent Protocol Specs
AI Analysis Layer
- AI Action Schema Generation Engine
- Draft WebMCP Actions
- Draft Structured Responses
Human in the Loop
- Engineer Review Session
- Actions Safe And Functionally Correct
- Flag Corrections To AI Engine
- Human Approved Action Set
Delivery
- Deployed To Production
- Agent Task Verification Test
- Client Sign Off
- Ongoing Task Success Monitoring
Integration-Heavy / Ecosystem-Connected Architecture
Client Systems
- Client E Commerce Or Booking Platform
- Inventory Or Availability System
- Payment Or Form Submission Backend
Agentic Core
- Agentic Optimization Engine
- WebMCP Action Model
- Structured Task Output
Two Way Sync Layer
- Inventory System Sync
- Booking System Sync
- Operations Team Dashboard
- Customer Service Dashboard
Shared Governance
- Joint Review With Engineering And Ops
- Production Agentic Endpoints Live
More in Answer & Generative Engine Optimization (AEO/GEO)
- AI Visibility Snapshot
A fast, low-cost scan of how a brand currently appears (or doesn't) across major AI answer engines.
- AEO Audit
The flagship diagnostic: hundreds of buyer-intent prompts sampled across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews to score citation rate, share of voice, and sentiment.
- AEO Competitor & Answer-Gap Audit
Benchmarks a brand's AI citation performance against named competitors and identifies exactly which questions it's losing.
- AI Question Bank & Search-Intent Mapping
Builds and prioritizes the exact set of buyer questions a brand needs to own inside AI answers.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start, scoped small enough to prove itself before you commit to anything bigger.
Talk to us about Agentic Search OptimizerMost engagements like this start as a $500–$2,500 pilot, see full pricing.