Maslow AIMASLOW|AI
BOOK SESSIONBOOK
OWNED INFRASTRUCTURE · KNOWLEDGE SYSTEMS · AI EMPLOYEES

AI employees for the work that waits on your busiest people.

Your files become knowledge your AI can cite. Your procedures become skills it can reuse. AI employees take on real workflows in Teams, Slack, and email — under accounts you control, with a person approving every consequential action. And everything we build stands on foundations you own.

BOOK A WORKING SESSIONTAKE THE 2-MINUTE ASSESSMENT
90 days
idea to working foundation — with go/no-go gates at weeks 2, 4, and 10
4 AI employees
live in one client's Microsoft Teams today
100%
of what we build is yours. No lock-in.
Fixed fees
priced in writing before we start
WHO WE WORK WITH

Built for the mid-market.

01
You run on Microsoft 365 or Google Workspace.
Teams, Slack, email, shared drives. Your AI should show up there, not in another tab nobody opens.
02
Your know-how lives in a few senior people.
Estimating, quoting, client intake, compliance answers. They're the reason you win work — and the ceiling on how much of it you can take.
03
You don't have an ML team, and you shouldn't need one.
We build systems your existing IT can run, and we stay until they can.

Typically $20M to $500M in revenue. If you need a global SI with a thousand consultants, we're not that. If your board runs a real vendor review, good — our diligence pack was built for exactly that.

NOT SURE IF THAT'S YOU? TAKE THE ASSESSMENT  >
IF YOU ALREADY PAY FOR COPILOT

Keep Copilot. Add the layer it's missing.

Rolling out Microsoft Copilot was the right call — it's the best personal assistant your people can have, and we'll tell you to keep it. What it structurally can't do is own a workflow: it doesn't know your estimating logic, can't carry a quote from request to approval across your systems, and doesn't answer from a knowledge base you govern. That's the layer we build. Most of our clients run both: Copilot for individuals, AI employees for the workflows.

SEE WHAT THE LAYER CONTAINS  >
THE CONCEPTS

Plain language, interactive proof

Each opens an interactive explainer
01Context engineeringDeciding exactly what your AI sees: the right data, structured and retrievable, at the right moment.EXPLORE  >
02Harness engineeringThe scaffolding around a model (skills, tools, memory, and guardrails) that turns raw intelligence into dependable work.EXPLORE  >
03Hybrid RAGYour unstructured files, converted into vector databases and knowledge graphs your AI can actually reason over.EXPLORE  >
04Virtual AI employeesAgents that live where your team works (Teams, Slack, email) and carry whole workflows, not just chats.EXPLORE  >
05Skills & gatewaysYour procedures, written once as reusable skills, shared by every agent, delivered through the channels you already run on.EXPLORE  >
06Local AIModels on your own hardware: private by default, with a flat monthly cost instead of a metered bill.EXPLORE  >
THE JOURNEY

Five stages. Enter at any of them.

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1
Assess
Find where AI actually pays.
2
Structure
Files become a vector DB + knowledge graph.
3
Build
Engineer the agentic harness.
4
Deploy
AI employees in your channels.
5
Own
Local models, flat cost curve.

GO/NO-GO GATES AT WEEKS 2, 4, AND 10 · STOP AT A GATE, KEEP EVERYTHING PRODUCED

NOT SURE WHERE YOU ARE? TAKE THE ASSESSMENTTAKE THE 2-MINUTE ASSESSMENT
PROOF

Real engagements, honest numbers

ALL CASE STUDIES  >
MANUFACTURING · REAL ENGAGEMENT
Infinite AI OS: an AI operating system in 90 days
Four named AI employees working in Microsoft Teams, standing on a six-layer root system: company memory, knowledge map, file intake, employee profiles, tool connectors, and observability.
4 AI employees live · 90 days to foundation
VIEW CASE STUDY  >
HEALTHCARE ENTERPRISE · REAL ENGAGEMENT
AgentHub: contracts you can question
A prompt library as the front door; behind it, a contract-review agent with hybrid retrieval and a citation on every answer.
Field-level citations · 50-document grounded corpus
VIEW CASE STUDY  >
YOUR OPERATION
Your operation could be the third card here.
One workflow, one channel, live in weeks. We'll map where AI pays in a 30-minute working session.
BOOK A WORKING SESSION  >
WHO YOU'LL WORK WITH

Maslow is led by Rakesh David, a former CIO/CTO who ran enterprise technology for twenty years — and founded Maslow to fix, from the vendor side, the key-person problem he kept meeting on the buyer side. You work directly with someone who has sat in your chair. And because everything we build lands in your repositories from day one, nothing about your system depends on any one person. Including him.

MEET THE FOUNDER  >
THE OTHER OPTION

Doing nothing has a price too.

Every quarter you wait: the quotes still queue behind one person, and the queue compounds. The know-how you most need captured gets one quarter closer to walking out the door. The files pile deeper, in formats only humans can search. None of that shows up as a line item — which is why it never gets fixed. The assessment takes two minutes and tells you whether AI pays in your operation. If it doesn't, we'll say so.

TAKE THE 2-MINUTE ASSESSMENT
“
Extraordinary AI shouldn't require an extraordinary budget.

Our mission is to reduce the cost of AI adoption: open models, local hardware, and engineering that outlasts any single model.

BOOK A WORKING SESSION