Lead-gen
Lead-gen agents — always-on SDR
Greet leads, ask smart questions, qualify fast, book meetings — without waiting for your team.
Pillar 02 / AI Agents
AI agent automation
actually do work
not just chat.
Autokrix builds AI agent workflows that read your data, make decisions, and take real actions across your tools. Lead-gen agents, support agents, and ops assistants — controlled digital teammates, not generic chatbots.
5–10hrs
Saved per person per week
From reduced repetitive messaging and follow-up
24/7
Coverage on leads and support
No more waiting until 9am Monday
2–6wks
Typical time to first live agent
Depends on scope and tools
What we mean by “AI agent”
Software that reads, decides, and acts — not just responds.
For example
“New lead replies → agent checks CRM → sees pipeline stage → sends the right follow-up → schedules a call → posts a summary in Slack.”
Reads
emails, messages, docs, and tickets — not just keywords, but actual meaning and context.
Decides
what to do based on your rules, policies, and business logic — not random guesses.
Acts
in your tools: sends replies, updates records, creates tasks, posts summaries — and logs every step.
Is this right for you?
When you need more than simple automation
Workflows follow fixed steps. AI agents make sense when the work needs reading, judgment, or back-and-forth. Here’s when that usually comes up:
- You get repetitive questions but the wording is different every time.
- Your team spends hours writing near-identical emails or replies, one by one.
- You need someone watching dashboards and inboxes, but only alerting when it matters.
- You want parts of your sales or support running 24/7, without hiring overnight staff.
- Your team handles routine tasks that need some judgment — not just button-clicking.
Two or more of these? You’re ready for an AI agent.
Under the hood
How Autokrix agents think and act
01
Context & meaning
We use modern language models so the agent understands the meaning of messages, tickets, and docs — not just keywords.
02
Rules and policies
On top of that: hard rules defining exactly what the agent can do, what it must check, and when it must hand off to a human. You write the rules; the agent follows them.
03
Tools and memory
Agents connect live to your tools — CRM, help desk, calendar, Slack — and keep full logs so you can see what they did and exactly why they did it.
Types of agents we build
Three kinds of AI teammates
Each agent focuses on one area — so it gets very good at that one thing instead of being mediocre at everything.
Support
Support agents — instant, on-brand answers
Handle common questions 24/7, draft replies for your team, and route complex issues without losing context.
Ops assistant
Ops assistants — your team’s internal helper
Watch inboxes, alerts, and tasks. Bring only the important things to humans, already with context.
Real agent examples
What these look like when built for your business
Not concept art. These are the specific agents we design and deploy.
Example 01 / Lead-gen Agent
From stranger to booked call — in under 2 minutes
Most leads go cold not because of price or quality — but because they waited too long for a reply. This agent fires the moment a lead makes contact.
How it runs
- Lead fills a form or replies to a campaign.
- Agent reads message and detects intent.
- Checks CRM for duplicates and prior context.
- Asks 2–4 targeted qualification questions.
- Good fit: offers booking link, updates CRM stage.
- Not ready: sends a relevant resource, tags for nurture.
- Posts a lead summary card to Slack for the team.
Pairs with: Lead Handling Workflow →
Example 02 / Support Agent
Instant answers on any channel, any time
Support agents don’t replace your team. They handle everything your team already knows the answer to — and free up people for the questions that actually need a human.
How it runs
- Customer asks a question via chat, email, or form.
- Agent detects intent and urgency level.
- Searches your docs, FAQs, and past resolved tickets.
- Generates a reply in your brand voice.
- High confidence: sends automatically.
- Low confidence: sends as a draft for team review.
- Tags and routes complex issues to the right queue.
- Logs the conversation for review and training.
Pairs with: Client Onboarding & Reporting Workflows →
Example 03 / Ops Assistant
Watching everything. Bothering you only when it matters.
Ops assistants are for the streams of alerts, emails, and system events your team ignores until something breaks. The agent filters, classifies, and acts — then sends a clean summary.
How it runs
- Agent monitors inboxes, dashboards, or system alerts.
- Groups related items, filters obvious noise.
- Reads each item and pulls out the key facts.
- Updates relevant tools (status, owner, priority).
- Creates tasks or incidents when thresholds are hit.
- Sends a plain-English summary to the right person or Slack channel.
- Tracks patterns to surface recurring issues for you to fix.
Pairs with: Operations & Back-office Workflows →
Safety and control
Every Autokrix agent ships with these guarantees
01
Guardrails first
We define exactly what the agent can and cannot do — which tools it touches, which data it sees, and which decisions need your approval before acting.
02
Human in the loop
For any high-stakes action — sending an email to a client, updating a deal value, flagging an issue — the agent asks first. Nothing important happens without visibility.
03
Full logs, always
Every input, every decision, every action is logged and readable. You can see exactly what the agent did and why — and tighten rules as trust grows.
Agents work best when your workflows are already solid
An agent that sits on top of messy, disconnected data gives messy results. We always look at the workflow layer first. If you haven’t automated the basics yet, that’s the right place to start.
Common questions
Questions before we build your AI agent workflow
Chatbots respond inside a chat window. Agents read context, make decisions, and take actions in your actual tools — updating records, sending emails, routing tickets.
No. It takes the repetitive, predictable work — so your team focuses on the conversations that genuinely need a human.
We ground every agent in your docs, policies, and past messages. We add review loops and test against real scenarios before going live.
We start with low-risk, human-approved actions. Everything is logged. We tighten rules based on what we see in the first weeks.
A focused agent for one channel or use case typically goes live in 2–6 weeks, depending on your data quality and tools.
Yes. Every agent has a clear off switch and falls back to standard workflows. You’re never locked in to the agent doing something critical.
Ready to start?
Let’s design your first AI agent workflow
In a 30-minute AI automation session, we’ll pick one area — leads, support, or ops — and sketch an agent that handles the repetitive work there with the right guardrails.
- One clear agent concept, written in plain English.
- Where it connects to your current tools and workflows.
- A realistic timeline and starting budget — no hidden complexity.
No pitch deck. No pressure. 30 minutes, then you decide.