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AI Agents That Run Your Sales Pipeline

Deploy a team of AI agents, researcher, qualifier, writer, scheduler, that work together to move leads from cold to closed.

Your sales process has too many manual steps

Reps spend more time on admin than selling

Lead research is manual and inconsistent

Follow-up sequences fall through the cracks

No personalization at scale, every email sounds the same

Pipeline visibility depends on reps updating the CRM

What We Implement

AI lead research agent

Automated lead qualification

Personalized outreach at scale

Multi-channel follow-up sequences

Automated meeting scheduling

Pipeline analytics dashboard

Our Process

01

Pipeline Analysis

We analyze your sales process, identify manual bottlenecks, and design the multi-agent architecture.

02

Agent Design

Build specialized agents: researcher, qualifier, copywriter, scheduler. Define handoff rules between agents.

03

Orchestration Build

Implement the orchestrator that routes leads between agents based on stage, score, and behavior signals.

04

Deploy & Optimize

Launch with A/B testing, performance dashboards, and continuous optimization of agent prompts and workflows.

Tools We Use

We select the best tools for your specific needs from our 45+ tool stack.

Frequently Asked Questions

How is this different from a single chatbot?

Multi-agent systems use specialized AI agents for each task. A researcher agent finds data, a qualifier scores leads, a writer drafts emails, each optimized for its role.

Can it work with our existing sales team?

Absolutely. AI agents handle the repetitive work while your reps focus on high-value conversations and closing.

How do the agents coordinate?

A central orchestrator routes leads between agents based on pipeline stage, lead score, and engagement signals.

What CRMs does it integrate with?

HubSpot, Salesforce, Pipedrive, and most CRMs. The system reads and writes deal data automatically.

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How PxlPeak Scaled Operations with AI Automation

As PxlPeak grew, the manual workload for lead qualification, content drafting, and client reporting became a scalability bottleneck. The agency was stuck in a high-headcount, low-margin trap, where every new client required a linear increase in manual labor. Additionally, our digital infrastructure lacked the technical hardening required for enterprise-level B2B sales, with fragmented systems and inconsistent data security protocols.

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VM Power Construction: 0 to 493 Organic Clicks and 212K Impressions in 90 Days

VM Power Construction & Remodeling LLC is the parent of a four-division Lehigh Valley contracting family: VM Power Construction (general remodeling, formed 2018 with founder Vincent Karaca's trade history since 2003), VM Power Decks (the legacy V&M Power brand since 2005), VM Power Exteriors (roofing, siding, gutters), and VM Power Flooring (hardwood, LVP, tile, refinishing). Each division operates independently, its own brand, phone, office, team, and website, while the parent LLC holds the licenses (PA HIC #158550, NJ HIC #13VH11744800) and the BBB A-rated profile with 448 reviews on Google. Despite 22+ years of trade reputation and a real customer base, the four division websites were ranking nowhere outside of direct branded searches. Schema across the four sites operated in entity-graph silos, no parent-child Organization references, conflicting NAP, fragmented aggregateRating placements, and zero shared content cluster. None of the four domains showed up for the high-intent informational queries (renovation cost, permit guidance, ADU regulations) that Lehigh Valley homeowners actually search before hiring a contractor. The core problem wasn't visibility, it was that Google had no way to recognize the four divisions as one credentialed family operating across six office locations.

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Put AI to Work for You.

Ready to implement multi-agent sales pipeline? Let's talk about your specific needs.

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