SERVICES / AGENTIC AI

AI agents that do the work.

Autonomous agents for revenue teams, built inside your stack, governed with humans in the loop, and measured against pipeline. Where most agencies advise on AI, we put it into production.

24/7
AGENT EXECUTION
0
ADDED HEADCOUNT
PRODUCTION
WHERE EVERY AGENT RUNS
TRUSTED BY 80+ COMPANIES
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OUR POINT OF VIEW

Most so-called AI agents are rule-based scripts in more sophisticated packaging. A genuine agent reasons toward a goal, selects its own next step, and recognizes when to stop and defer to a human. We build one only when the work is genuinely unpredictable, and we keep a person in command of anything that touches a customer or a budget.

THE GAP

The manual work gap

Revenue teams lose their week to research, data entry, and handoffs between systems. Agents take the repetitive execution, so your people keep the judgment.

60-70%
Most work hours are automatable

Today's generative AI and automation technologies could take on activities that absorb 60 to 70 percent of employees' working time.

McKinsey, The Economic Potential of Generative AI 2023
70%
Sellers barely get to sell

Sales reps spend 70% of their time on non-selling tasks like admin work and meeting prep instead of talking to customers.

Salesforce, State of Sales 2024
15%
Agents start making decisions

Gartner predicts at least 15% of day-to-day work decisions will be made autonomously by agentic AI by 2028, up from 0% in 2024.

Gartner, press release 2025
PROOF

Case Studies

See which workflows an agent should own first.

Book a strategy call →
CAPABILITIES

What's included.

01

AI SDRs & Outbound Agents

Pipeline at machine volume, personalized precisely enough to earn the reply.

Agents research target accounts, read live buying signals, and compose outbound personalized to each contact, booking meetings your reps close. A human approves every message before it sends.

02

Marketing Ops & Personalization

Campaigns monitored around the clock, experiences tuned to every visitor.

Agents catch spend drift or a broken pixel the moment it occurs, rebalance budgets toward what is performing, and deliver reporting on demand. On site, offers adapt to each visitor in real time, attributed to revenue.

03

Custom Assistants & Automation

Internal tools on your data, and a stack integrated so manual handoffs disappear.

Claude- and GPT-powered proposal writers, research copilots, and knowledge assistants run on your data with scoped access. Your CRM, ad platforms, email, billing, and warehouse connect into workflows that keep every record in sync.

04

Agent Evaluation & Guardrails

Guardrails, monitoring, and approval gates on every agent we ship.

Every agent ships with an evaluation suite that scores output against real examples before production. High-stakes actions pass through human approval gates, and every action is logged and auditable.

HOW WE WORK

The method.

01
Map the Manual Work

We map every manual workflow across your revenue team and rank each by return. You get an automation plan that names which work agents should own, in order.

02
Design the Agent Roster

Each agent is scoped like a hire: a defined role, scoped data access, a clear escalation path, and one success metric tied to pipeline.

03
Deploy Into Your Stack

Agents ship into your CRM, ad platforms, warehouse, and Slack. The highest-return workflow goes live first, so value arrives early.

04
Govern with Evaluations

Approval gates on every high-stakes action, evaluation suites scoring output continuously, and monitoring that surfaces drift before it reaches your numbers.

05
Enable & Expand

Every workflow documented, every operator trained. Retain us to grow the roster, or run it yourself. Either way, you own it all.

WHY EGGKNITE

Core Differences

EGGKNITEHiring headcountDIY automation tools
CapacityAgents run around the clock, and scaling volume is a configuration change.Capacity grows one salary at a time, with ramp on every hire.Capacity capped by whoever maintains the Zaps on the side.
Scope of workResearch, personalization, monitoring, and reporting handled end to end, with judgment escalated to a human.Full human judgment, spent mostly on repetitive execution.Fixed if-this-then-that paths that break on the first exception.
Quality controlEvaluation suites, approval gates, and drift monitoring on every agent we ship.Manager review, when there is time.Silent failures discovered weeks later.
MeasurementEvery agent carries one success metric, reconciled to pipeline in your dashboards.Activity tracked in one-on-ones and CRM hygiene reports.Run counts, with revenue impact unknown.
OwnershipYou own the agents, the data, and the playbook, documented and current.Knowledge walks out the door with turnover.A tangle only its builder can maintain.

Give your team its week back.

Book a strategy call →
WHAT YOU GET

Deliverables that ship.

An agent roster in production: named agents with defined roles running inside your tech stack
Outbound infrastructure that researches accounts, personalizes from live signals, and books meetings your reps close, with a human approving every send
Continuous reporting that reconciles agent activity to pipeline and revenue, refreshed the moment your team needs it
Evaluation suites and guardrails on every agent, with human approval gates on anything that touches a customer or a budget
Full documentation and operator training, kept current as the agents evolve, so your team runs the system with confidence
A FIT WHEN
  • Your pipeline must grow while headcount stays fixed, and output has to scale without adding people.
  • Your RevOps queue is full of intent signals no one can act on quickly enough, and the opportunity cools before a play reaches market.
  • You have run AI pilots that never reached production, and you want agents operating for real inside your stack.
  • Your revenue team loses hours each week to manual transfers between the CRM, ad platforms, and spreadsheets that should never require a person.
  • You need a custom agentic AI solution designed around a workflow unique to your business.
FAQ

Questions, answered.

A rule-based automation follows a fixed path: if this happens, do that. A generative tool answers a prompt and then stops. An agent sits above both: it holds a goal, reasons about how to reach it, chooses its own next step from the tools available, and knows when to hand off to a human.

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