AI agents for marketing, sales & growth
AI Agents that Already know your Business
We build agents that learn your business, adapt to how your team operates, and share context with each other. We don't replace what's working. We make it faster and smarter.
The problem
Built to demo well. Not to run well.
Most AI agent setups break for the same three reasons.
Generic agents. Generic results.
Your agent was trained on the internet. It doesn't know your product, your pricing, or why your last campaign worked. So it writes like everyone else.
You rewrite everything — and wonder why you pay for AI.
An agent that doesn't know your business is expensive autocomplete.
No shared context. Each agent works from a slice.
Your research agent learns customers care about price, not speed. Nothing carries that to your ad agent.
The same objection lands weekly — your FAQ still ignores it. Each agent works from its own thin slice.
You don't have an AI problem. You have a context problem.
Knowledge trapped everywhere except where it's needed.
Your best campaign teardown sits in a doc nobody opened since March. Your objection playbook lives in one rep's head.
None of it reaches your AI.
Your org knowledge is scattered across 14 tools and 6 people's heads.
How we build
Four steps. One system.
The order matters. Each step depends on the one before it.
Step 01
Find what matters
We audit how your team actually works — not how it should work on paper. We identify the 2-3 workflows where agents will have the highest impact. Not a 40-page roadmap. A focused plan you can act on in weeks.
Step 02
Build the knowledge layer
Before any agent goes live, we build what it will think with. Your brand rules, customer research, campaign history, sales objections, product docs — pulled from your existing tools and structured so every agent can access it. This layer grows over time as agents add what they learn.
This step is what everyone else skips. It's also why their agents produce generic output and ours don't.
Step 03
Build agents that fit
Purpose-built for your workflows. Not templates, not wrappers. Each agent reads from the knowledge layer before starting and writes back after completing. Your research agent doesn't produce a generic report. It produces a brief your ad team can act on the same day.
Step 04
We operate. You direct.
Agents connect to your CRM, ad platforms, email tools, analytics. We handle deployment, monitoring, and improvement. When the knowledge layer surfaces a new pattern, we act on it. You review outputs and set priorities. The system gets sharper every month.
Use Cases
Five use cases. Each one connected to your data.
Anyone can wrap an LLM. The difference is what it reads, what it acts on, and what it writes back.
Use Case 01
User Research
Stay on top of what users say about your product. Learn their pain points, their language, their frustrations — across every channel they use. Structured into an intelligence layer every other agent reads.
Use Case 02
Customer Support
Not another chatbot. An AI support agent — privacy-first — that resolves repeat tickets, routes unknowns to humans with full context, and feeds every resolution back. The knowledge base improves itself.
Use Case 03
AI Visibility & SEO
Monitor your brand across ChatGPT, Gemini, and Perplexity. Find where you're cited, where you're invisible, and why. Then build the content that closes the gap — for both Google and AI search.
Use Case 04
Performance Marketing
Daily ad decisions grounded in research signals. Hooks sourced from what users actually say. Every test logged. Every learning inherited by the next brief. The system compounds.
Use Case 05
Sales Intelligence
Lead arrives. Enriched with company research and first-party data. Scored and routed instantly. Rep closes or gives feedback. The scoring model improves. Every cycle, the system gets sharper.
What makes them work
Not wrappers. Not templates. Agents built for your business.
Five things separate our agents from what you've tried before.
Integrated with your data
CRM, ad platforms, docs — connected from day one.
Every agent connects to your tools from day one — CRM, ad platforms, analytics, docs, spreadsheets. No copy-pasting context. Your data stays where it lives.
Multimodal by default
Text, images, PDFs, dashboards.
They process dashboards, PDFs, images, call recordings, spreadsheets. A research agent reads a competitor's landing page. A support agent parses a screenshot.
Fine-tuned to your business
Your tone, your terminology, your edge cases.
Calibrated to your tone, terminology, and edge cases. Trained on your brand guidelines, top content, and sales playbook - output sounds like your team wrote it.
Autonomous. 24/7.
Monitor, act, escalate — round the clock.
Agents don't wait for a prompt. They monitor, act, and escalate on their own. Reddit thread at 2am? Caught. Form fill at midnight? Scored and routed.
Connected to your channels
Slack, Gmail, WhatsApp — work finds you.
Agents deliver where your team already works. Slack when a brief is ready. Email when a lead scores high. WhatsApp for time-sensitive comms.
Weekly customer research report shared
User research agent • 2m ago
Lead routed to Priya
Routing Agent • 12m ago
Frequently asked questions
Everything you need to know.
What Layerz is
How is this different from ChatGPT or other AI tools?
Those are tools you prompt. Our agents run on your workflows, read from your data, and operate without supervision. You don't log in and ask questions. Agents run, produce output, and surface what matters.
What's the knowledge layer?
It's the structured business context every agent reads from before acting and writes back to after completing work. Brand rules, campaign history, customer research, sales objections, product docs — pulled from your existing tools and organised so any agent can use it. It grows over time as agents add what they learn. It's the step most agent vendors skip, and the reason their output stays generic.
How is this different from hiring an AI development agency?
Most dev shops build what you spec and walk away. We build and operate. The agents keep running, the knowledge layer keeps growing, and we tune the system every month. You don't inherit a codebase. You get a working system.
Do you replace my marketing or sales team?
No. We replace the vendors and tools around them. Your team owns strategy and judgment. Agents handle the execution, research, and repetitive work that buries your best people.
Do you work with companies in our industry?
We work across industries. The agents are built for functions — marketing, sales, growth, support — not verticals. The knowledge layer is what makes each deployment specific to your business.
Trust & control
What if an agent produces something wrong or off-brand?
Human review is built into the early phases. You set the guardrails — tone, claims, compliance rules. Autonomy increases as trust builds. Nothing goes out without your approval until you say otherwise.
Is our data safe?
Your data is not used to train models. Access is role-based and audited. We work within your security and compliance requirements — SOC 2, DPAs, data residency. We'll cover specifics on the strategy call.
What data do you need access to?
Whatever the agents need to do their job. CRM, ad accounts, analytics, helpdesk, docs. We connect through standard integrations — not bulk exports, not database access. Your data stays in your tools. Agents read it where it lives.
What happens to our data if we stop working with you?
It's yours. The knowledge layer, the agent configurations, the assets — everything exports. You leave with everything we built. No lock-in.
Getting started
How long until we see results?
First agents go live within weeks. The knowledge layer builds over the first few months. The system gets measurably sharper as it accumulates data — month two is better than month one, and month six is better than both.
Can we start small?
Yes. That's how we work. We start with one high-impact workflow, prove it works, then expand. No big bang. No 6-month roadmap before anything goes live.
What if we don't have clean data or documented processes?
Some messiness is normal. We audit what you have and structure it during the knowledge layer build. But if there's no process at all — no campaigns, no sales motion, no support function — agents don't have anything to enhance. We'll be honest about that upfront.
What if we already tried AI agents and they didn't work?
That's most of our clients. The usual failure mode is the same: generic agents, no shared context, no grounding in your business data. The knowledge layer is specifically what fixes that. The first call usually makes the difference clear.
Pricing & commitment
How are you priced?
Against the stack we replace — not per seat, not per agent, not per token. On a strategy call, we'll scope what you need and price it against your current spend on tools, vendors, and manual work.
What's the minimum commitment?
We'll cover this on the strategy call. There's no 12-month lock-in. But the system compounds over time — teams that stay longer get disproportionately more value because the knowledge layer keeps growing.
Get in touch
Let's build something that knows your business.
Tell us about your workflow. We'll come back with a focused plan — not a pitch deck.
- No sales calls until you want one
- We respond within one business day
- First session is a strategy call, not a demo