001 · Practical AI Systems · Since 2024

Your business doesn’t need
more AI tools.
It needs better systems.

We build AI systems that run inside real businesses, including our own. The first step is a 14-day Workflow Diagnostic on the workflow that’s hurting most.
La Crosse, WI · Est. 2024
Fig. 01 — Operations at rest ↓ scroll
AI Workflow Audit Infrastructure Setup Workspace Install Monthly Cadence AI Workflow Audit Infrastructure Setup Workspace Install Monthly Cadence AI Workflow Audit Infrastructure Setup Workspace Install Monthly Cadence
01
— The Problem

Most businesses are using AI badly.

Too many subscriptions. Follow-up that gets dropped. Reporting that eats half a day every week. Knowledge lives in one person’s head.

AI gets used in pockets — a prompt here, a tool there — but never becomes part of how the business actually runs.

The problem isn’t the technology. It’s the lack of a system.

Fig. 02 Workflow mapping on-site
Fig. 03 Retrieval topology
No. 04
Less
tooling,
more system.
↓ how we work
02
— Our Approach

We start with your workflow, not the technology.

Learn how it works →

Most consultants lead with tools. We lead with working systems: a client assistant in daily production use, plus the agents, CRM, and reporting fleet that runs our own back office. We map where your time and money actually go, then build the system around what the map shows.

Map First
Understand before we build
System > App
Workflows, not subscriptions
Built to Last
Postgres-backed, multi-model
Owner Out
Break the single-point bottleneck
03
— What Actually Changes

From scramble, to system.

— Before
Reporting takes hours every week
Follow-up depends on someone remembering
Knowledge lives in one person’s head
AI usage is scattered across random tools
The owner is the bottleneck for every decision
— After
Reporting runs itself
Follow-up happens automatically
Knowledge is captured and accessible
AI works inside your actual workflows
The team has visibility and can move
04
— Built & Running

Systems shipped. Running now.

A sample of what’s been built and put into production — what each system replaced, and what runs in its place.

01 Client · Javeri & Co.
Client-relations assistant

An AI assistant for a jewelry retailer that tracks repairs, sends timed client reminders and follow-ups, and handles day-to-day client messaging over Telegram. It runs on cost-efficient local models, with cloud models reserved for the work that needs them — hardened over months of daily production use and wired into the store’s e-commerce operations.

Replaced repair status and follow-up carried in someone’s memory
Runs now reminders and messages that fire on schedule, every day
02 Product · Atticus
Family support assistant

A support assistant for families of children with developmental disabilities. Its hand-verified knowledge base covers programs and resources across all 51 US states and DC, with guided onboarding and deadline tracking — and strict write-guards so it can never claim an action it didn’t take. PostgreSQL backend, privacy-first by design.

Replaced scattered, out-of-date program information
Runs now a verified knowledge base with guarded, honest answers
03 Pilot · TradeScribe
Field work-order capture

A pilot for an electrician that turns voice memos from the field into documented, timestamped work orders — each one anchored to a tamper-evident evidence chain with cryptographic hashing. Built provider-agnostic and delivered as a completed pilot.

Replaced notes written up after the job, if at all
Delivered voice memos becoming verifiable, timestamped records
04 Reference Build · In production
The operations fleet

Our own back office: a set of AI agents running client CRM, product-catalog sync, monitoring, and weekly reporting 24/7. Local open-weight models carry the bulk of the load; cloud frontier models are routed in through a broker only where they earn their cost. It’s the same cost-routing architecture the industry started marketing in 2026 — in production here first.

Replaced manual ops and one-off scripts
Runs now a hybrid, tiered system that audits itself
Read the full teardown →
05
— Services
01 / Start here 14 days · $2,000 flat
Workflow Diagnostic
One workflow, one location, fourteen days. We map where the time and money leak and hand you the map of the automation worth building. The fee credits toward your next engagement, and if the map can’t find you five hours a week, it’s free.
02 / Service 5–7 weeks
Infrastructure Setup
Workspace, visibility, security, architecture. The foundation everything else sits on.
03 / Service 9–13 weeks
Workspace Install
The full working system — workflows, automations, reporting, team training.
04 / Service Ongoing
Monthly Cadence
A structured monthly rhythm that keeps your AI capability improving over time.
06
— Who This Is For

If two or more of these sound familiar, we should talk.

01.
You’ve bought AI tools nobody uses
02.
Follow-up depends on someone remembering
03.
Reporting eats a day every week
04.
Critical knowledge lives in one person’s head
05.
You know AI should help — nothing has stuck yet
⊗ Not a fit
If you’re looking for a chatbot, a one-time workshop, or AI without guardrails — we’re not the right fit. And that’s okay.
We say no a lot. It’s how we protect the work.
07
— Who’s Behind This
Mikhail Zaidi Founder
“The businesses that win with AI won’t have the best prompts. They’ll have the best systems.
SteadyFrame is built on hands-on experience shipping AI-powered tools that solve operational problems. CRM and follow-up systems, retrieval layers, multi-model setups, Postgres-backed architectures, and the orchestration logic that ties it all together.
Mikhail Zaidi Founder & Principal La Crosse, WI
08
— Next Step

Stop bolting AI on.
Build the system.

A 30-minute scoping call to confirm fit. If we go forward, the first engagement is a 14-day Workflow Diagnostic: $2,000 flat, one workflow, the map is yours either way. The fee credits toward the build if we keep going, and if the map doesn’t find you five hours a week, it’s free.