AI Agents & Automation

A 47-Hour Delay Kills the Deal. An AI Agent Responds in 30 Seconds.

The average response time to a web lead is 47 hours. Most leads go cold after 5 minutes of no response. An AI agent covers the hours when people cannot.

73%

of leads are not contacted by any vendor — they just disappear

Losing leads at 2am because no one's there to respond? Spending hours on repetitive tasks that a robot could do? Your competitors are already using AI to work faster.

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24/7 AI Coverage

Channels in

Actions out

Website Chat

Phone

Lead Qualified

Appt. Booked

CRM Updated

Support Resolved

On10 AI Agent

Answering · 24/7/365

handled today · 30s avg

Website Chat

Phone

Lead Qualified

Appt. Booked

CRM Updated

Support Resolved

On10 AI Agent·Answering 24/7·48handled today

The Problem

Every lead that arrives after 5pm is already cold by morning.

A prospect fills out a form on your website at 9pm on a Friday. Your team sees it on Monday. The prospect has already moved on to the next option. Your competitor had a bot that responded in 30 seconds. Whose offer do you think the prospect is considering?

Most contact entry points (web chat, email, phone) do not have 24/7 coverage. Hiring staff to answer phones at 2am is not economical. An AI agent handles the volume, qualifies the prospect, and books the appointment. When the prospect is ready to talk to a human, you are there.

Losing leads at 2am because no one's there to respond? Spending hours on repetitive tasks that a robot could do? Your competitors are already using AI to work faster.

90%

of businesses have no response infrastructure for leads that arrive outside business hours

Our Approach

The Agent Fit Framework

Most AI agent builds fail because the organization did not define what the agent should actually do. We define that before building. Three phases of design before any code is written.

Map Contact Entry Points

Where do leads and customers initiate contact? Website chat, email, phone, social messages. Which channels get the most volume? Which channels are understaffed?

Qualify the Conversation

What does the AI need to know to qualify a prospect (good fit or not), route them to the right person, or resolve without escalating? Budget, timeline, specific need, contact info.

Define Handoff Protocol

Exactly when and how does the agent escalate to a human? What context does the human need? What channel does the conversation move to? The handoff design is as important as the agent design.

How We Engage

Find the Right Fit

Three ways to work with us — choose the scope that matches where you are.

Agent Diagnostic

1 week

Businesses considering AI agents but unsure where to start.

Assessment of contact entry points and volumes
Response time analysis (how long until leads are contacted?)
Lead qualification gaps (what questions are not being asked?)
Agent design blueprint (conversation flows, escalation triggers)
ROI estimate (cost to implement vs. leads recovered)

Single Agent Build

4-6 weeks

Clear entry-point problem (e.g., unanswered leads after hours).

Agent design and conversation flow documentation
Deployed AI agent on primary contact channel
CRM integration (lead created, tagged, routed on handoff)
Handoff protocol to human team
Team training and documentation
30-day post-launch review

Multi-Channel Agent Program

12-16 weeks

High contact volume across multiple entry points.

Multiple agents (web, email, text, social)
CRM integration and lead routing
Customer support resolution bot (when appropriate)
Weekly performance reviews
Continuous optimization and improvement
Quarterly strategy sessions

What We See Every Time

3 Things That Hold AI Agents & Automation Back

These are not edge cases. We see all three in almost every engagement.

The First Agent Built is Almost Never the Right One

Teams default to a customer-support bot because it feels safe and low-risk. But the highest-ROI placement is almost always lead qualification — the revenue-generating contact point. Support bots save staff time. Lead-qualification agents generate revenue. Start at the top of the funnel.

Handoff Protocol Breaks the Whole Thing

A great agent that hands off poorly — wrong timing, no context transferred, wrong channel — creates worse customer outcomes than no agent. A prospect chatting with a bot who gets "please wait for an email" is frustrated. The handoff design matters as much as the agent design.

Speed Beats Sophistication

Teams want a complex agent that can handle everything before proving the simple one works. A basic agent that responds in 30 seconds, collects details, and books an appointment outperforms a complex agent that takes 3 months to build. Start narrow, prove ROI, then expand.

Client Results

What This Service Is Built to Deliver

Case study for this service is being finalized. Book a consultation to hear about client outcomes directly.

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Your Deliverable

What You Get at the End

Concrete artifacts you own and can act on immediately.

Agent Design Blueprint — Conversation flows, escalation triggers, and handoff protocol.

Deployed AI Agent — Live agent on your primary contact channel, trained on your content.

CRM Integration — Agent conversations create leads in CRM with proper tagging and routing.

Handoff Protocol — Documentation for your team on how to handle agent handoffs.

Performance Dashboard — Conversations, qualification rate, booking rate, and escalation tracking.

30-Day Review Session — Retrospective on what is working and optimization priorities.

Sample Deliverable

Action Items

Timeline

AI Agents & Automation · On10 Solutions

Common Questions

Before You Start

Answers to what prospects ask us most before booking.

What platforms do you build agents on?

We build on multiple platforms: Zapier, Make, n8n for workflow automation, or custom LLM-based agents using OpenAI or Claude. Choice depends on complexity and integration needs. We recommend the platform that gives you the best long-term ownership.

Will the agent sound like a robot?

No. We write the agent voice to match your brand. Conversation flows are natural, not scripted. The agent listens, clarifies, and adapts. Modern LLMs sound conversational. The agent is trained on your content and tone.

How does the agent know when to escalate to a human?

We define escalation triggers in the agent design: if the prospect says "I want to talk to someone," or if the question falls outside the agent scope, or if sentiment becomes frustrated, the agent escalates. You control the rules.

What happens if the agent says something wrong?

It happens. We review agent interactions weekly and refine the instructions. The agent learns from mistakes and improves. You can also intervene on specific conversations if needed. The agent is supervised, not autonomous.

How do we update the agent when our services or prices change?

Updates are simple: we update the training data or knowledge base. Depending on the platform, updates take hours to days. Not complex changes — just refresh the source material.

Can the agent handle both sales AND support?

Not well. An agent trying to do both is a compromise on both. We recommend separate agents: one for lead qualification (sales), one for customer support (service). They can operate on the same channel, but conversation flows differ.

How do you measure whether the agent is actually performing?

We track: conversations per week, qualification rate (% of conversations that result in a lead), booking rate (% that book a call), escalation rate (% that need human), and sentiment. ROI is: leads recovered × conversion rate × deal size minus agent cost.

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