AI studio for operations

AI systems that run real businesses.

We diagnose your operation and build agents and systems that answer, quote, and follow up alongside your team, on top of the tools you already use.

Your team, powered by agents; people approve.

Start the guided diagnostic See how it works

Demo · lead → agent → follow-up → human

Illustrative conversation. A lead writes on WhatsApp; the agent asks three qualifying questions, classifies the lead as qualified, schedules the follow-up, and hands off to a salesperson with a written summary. A human approves before the next reply goes out.

Lead
Agent
Follow-up
Human

WhatsApp · inbound lead

LeadHi — do you furnish offices? We're moving to a new floor, about 40 desks.
Agent · Q1Thanks for reaching out. Is this a new fit-out or a replacement of current furniture?
LeadNew fit-out. The floor is empty.
Agent · Q2When do you need the team seated?
LeadMove-in is early March.
Agent · Q3Who else is part of the decision?
LeadMe and our operations manager.

Classified · funnel stage

New
Engaged
Qualified
Proposal
Closed

High intent · 3 of 3 questions answered

Follow-up · scheduled

Floor-plan request sent, site-visit link offered. Reminder in 48 h if there is no reply.

Handoff · sales

Need: 40 desks, new fit-out
When: Move-in early March
Who: 2 decision-makers
Next: Floor-plan review call

Human approved the next reply

Verified figures

50+enterprise clients
77+industrial plants
9+years in industrial AI

How it works

From first message to close, with a person at every decision.

This is how an IteraAgents agent works with your team. It is the path of our illustrative demo and of the first client deployment, now pre-launch.

Step 01
A lead arrives
They write on WhatsApp, Messenger, or Instagram, at any hour.
Step 02
The agent replies
It answers the first message with information you have approved.
Step 03
It qualifies
Three questions, then the lead is placed in a funnel stage.
Step 04
Unified channels
All three channels follow the same flow and land in one record.
Step 05
Updates your system
It logs the stage and summary in your funnel or CRM, per scope.
Step 06
Schedules
It sends the booking link or schedules the follow-up.
Step 07
Follows up
It reminds leads who went quiet and reactivates past customers.
A person approves
The agent hands over the conversation with a written summary, and a person decides what goes out next.

One day of operation, before and after

Messages

BeforeMessages go unanswered at night and on weekends; follow-up depends on memory.

With the systemThe agent answers, qualifies, and schedules the follow-up; a person receives the summary.

Quotes

BeforeEach quote is put together by hand, hunting prices across scattered lists.

With the systemAssisted quoting: AI drafts the quote and a person approves it before it is sent.

Data

BeforeCustomers, prices, and expenses are spread across loose files with no reliable backup.

With the systemOne source of data, with role-based access and automated backups.

Visibility

BeforeNo one can see the whole business at once.

With the systemEach person sees their slice of the flow, and the owner sees it end to end.

Illustrative comparison based on the documented cases. Results vary by scope, data quality, and operating conditions.

Solutions

One method per type of business. The data and the rules change.

Pick your type of business. Each one runs through the same four stages and shows the real reference behind it, with its status.

For industrial and spare-parts distributors

From request to quote, and from quote to cash.

AttractPaid media operated through the ads API, with creatives built from your catalog.
ConvertA request by email, message, or PDF becomes a quote ready for review.
OperateEnriched catalog, supplier price lists, field service, and an ERP finance mirror, with role-based access.
ScalePrice benchmarking against the market and measured response capacity to decide the next module.

Industrial equipment distributor (Mexico)Production-deployed · operated with the client team

Read the case

Flow · from message to document

A customer asks on WhatsApp for a quote. The commercial operating system's AI orchestrator parses the request, matches it against the catalog, and composes three documents — quotation, spec sheet, and price list — ready for human review in 42 seconds.

Illustrative example. The 42-second figure is from production.

Other industries with the same problems are application examples, not proven specialties; we say so in the diagnostic.

Results

Figures with a source. Each one names its case.

We only publish figures measured in a real system or in a documented role. None of them is a promise for your operation.

42 sec
From request to a quote ready for review
A real customer request, in production; it used to take days. A person reviews before it is sent.
Source: Industrial equipment distributorRead case
2–4 mo
Enterprise sales cycle
With the pre-sales assessment platform; down from 8+ months.
Source: Pre-sales platform · prior roleRead case
+60%
Sales-process satisfaction
CSAT after the pre-sales assessment platform went live, used with 50+ enterprise clients.
Source: Pre-sales platform · prior roleRead case
To the cent
Collections reconciled against the ERP
The finance module mirrors the client's ERP sales, expenses, and monthly collections; it does not replace it.
Source: Industrial equipment distributorRead case
368
Enriched catalog items
With AI-generated spec sheets and 190 AI-enhanced product photos.
Source: Industrial equipment distributorRead case
13
Machines in our microfactory
11 FDM printers, 1 SLA, and 1 laser run on the same system we implement for clients.
Source: IteraShop² · in-house ventureRead case

50+modules in production in a role-based portal
900+automated tests guarding every change
95ad creatives in the internal gallery
6weeks to the first version in production

Counters from the industrial distributor case. Results vary by scope, data quality, and operating conditions.

Platform

Four pillars, one system. Agents at the center.

You start with the pillar that solves your bottleneck and add the others when your own numbers show the evidence.

IteraAgentsCore

WhatsApp agents that work your leads

Agents that qualify inbound leads, follow up automatically, and reactivate past customers on WhatsApp and Messenger — with a human approving what matters and receiving a clean summary at handoff.

Lead
Agent
Follow-up
Human

QualificationFollow-upReactivationHuman approval

Read the IteraAgents file

IteraConsulting

Assessments, advisory, and data analysis

An evidence-based read of your operation before anything is built: structured assessments, analysis of your historical commercial data, and advisory on what to automate first — and what to leave alone.

IS2 diagnosticHistorical-data analysisAdvisory

See how we work

IteraMarketing

Operated paid media

Paid social operated as a system: creatives composed from your catalog, campaigns run through the ads API, and results read against real conversations — not vanity metrics.

Meta Ads APICatalog-driven creativesConversion data

See the demand engine

IteraSystems

Systems and micro-systems on our chassis

From a single focused tool to a full commercial operating system — quoting, catalog, pricing, finance mirrors, role-based portals — built on a production chassis we already run, so you start from proven parts.

Quote-to-cashMicro-systemsRole-based accessBackups

See a system in production

Start small, scale by evidence.

Every engagement starts at an entry door and moves up one rung at a time — only when the previous rung has shown results in your own numbers.

Entry doors

Agent demo on your use case (free)
Historical-data analysis
IS2 diagnostic

AgentOne agent on one channel, working real leads.
Agent + dataThe agent reads and writes your commercial data.
DemandOperated paid media feeding the agent.
Micro-systemA focused tool for the next bottleneck.
Integral caseA full commercial operating system.

Why IteraSystems

Concrete reasons, not promises.

9+ years in industrial operations
77+ plants seen across product and technical-commercial roles. We understand how a business quotes, produces, and collects before we propose an agent.
- Industrial distribution
- Contractors
- Services
- E-commerce and own brands
A person approves
Agents take the repetitive work; quotes, sensitive replies, and publications go through a person.
Proven in-house first
IteraShop², our microfactory, runs on the same system we implement. The lab comes before the client.
Weeks, not quarters
The first version reaches your team in weeks, with the timeline set in writing after the diagnostic.
Your data and code are yours
At the end of an engagement, code, data, and documentation can be handed over in full.
Works with what you use
WhatsApp, spreadsheets, your ERP or CRM, and your ads account, through their APIs or exports.
Backups and role-based access
Each person sees only their slice, backups are automated, and every agent action is logged.
Closed scope in writing
Which modules, in what order, and what is out, before we build. No open-ended projects.

Assisted quoting

The quote goes out in minutes, and a person approves it.

The pattern running in production with an industrial distributor, in miniature. Try the demo: it uses an illustrative model and shows no real prices.

Reads the requestEmail, message, or PDF: AI extracts product, quantity, and conditions.
Applies your rate cardThe draft comes from your price lists and margin rules, not invented figures.
A person approvesNothing goes out unreviewed: it is approved or sent back to the request with a note.

Start the guided diagnostic

Interactive demo with illustrative data.

Live demo · illustrativeLive — illustrative model

RFQ intake

AI draft

Human gate

Quote out

Live demo

Quote a part, end to end

The same intake → draft → human-approval pattern our production systems run, in miniature. Spec a part; a deterministic, illustrative pricing model drafts the quote and a human gate signs it off. Demo figures only — no customer data.

Quotation — awaiting RFQ

FDM · PLA · M envelope · as-built · 25 pcs

Submit the RFQ on the left — the model drafts a quote instantly and routes it through the human gate before anything goes out.

Work

Built, shipped, and operated. Each with its real status.

Anonymous case files with the exact status of each system, including the engagements in flight in the US.

IteraShop² — in-house ventureMade-to-order manufacturing and own brands
In production · in-house
A make-to-order microfactory that runs on its own agentic operating system
Our digital manufacturing venture integrates the chain from demand to the shop floor — CNC, 3D printing, and laser — on an operating system we built for ourselves. It makes real physical product to order: decorative lighting, branded stamps, cutters and rollers, automotive and marine parts, and industrial fixtures. It is the proving ground where our stack earns its way into client work.
13Fabrication machines — 11 FDM printers, 1 SLA printer, and 1 laser
Read case
Industrial equipment distributor (Mexico)Industrial distribution
Production-deployed · operated with the client team
Quote-to-cash: a commercial operating system for an industrial equipment distributor
An industrial equipment distributor ran its business on spreadsheets, paper, and chat. A quote-to-cash operating system now covers lead → quote → order → service → after-sales in one role-gated portal, with finance mirrored from the ERP and paid media operated through the ads API. Production-deployed and operated with the client team.
50+Operational modules in one role-gated portal, lead to after-sales
Read case
IteraAgents — lead agentsServices with high message volume
Capability verified · first deployment pre-launch
WhatsApp agents that qualify, follow up, and hand off to a human
A lead agent that answers inbound messages on WhatsApp and Messenger, qualifies with a short set of questions, places the lead in a funnel stage, schedules the follow-up, and hands off to a person with a summary — with human approval where it matters. The capability is verified; the first client deployment is built and in pre-launch.
3Qualifying questions before a lead is classified
Read case
Industrial AI SaaS · pre-sales platform (prior role)Software for manufacturing
Delivered in a prior role · 50+ enterprise clients
A pre-sales assessment platform that cut the enterprise sale to months
Designed while leading the technical side of the commercial team at an industrial AI SaaS: a structured process assessment, an ROI simulation, and a personalized demo built from the prospect's own inputs. Used with 50+ enterprise clients, it shortened the sales cycle from 8+ months to two to four months and raised sales-process CSAT by 60%.
50+Enterprise clients assessed with the platform
Read case
Demand-generation systemDemand generation
In operation · paid media via API
A marketing engine that turns a product catalog into demand
A system that runs digital demand generation across paid social, outbound, and a partner program — generating ads, pricing, and copy straight from the product catalog through API automation, with a human approving every publication. Built as a reusable layer, it feeds both the distributor portal and IteraShop².
3Demand channels run as one system — paid social, outbound, partner program
Read case
Sign & graphics company (Houston, TX)Signs and graphics
Building · agent built, pre-launch
Lead agent on WhatsApp, Messenger, and Instagram
Qualification, automatic follow-up, reactivation of customers from the last one to three years, and an appointment link — with a human taking over when it matters.
In flight · US
Commercial glazing contractor (Houston, TX)Contractors · commercial glazing
In discovery
Supplier specs, price comparison, and assisted quoting
Curtain wall and storefront work: supplier spec sheets and price comparison per vendor, assisted quoting, and quoted-versus-actual close — on top of the tools the team already uses.
In flight · US

Active engagements in Houston, shown anonymously and with their real status.

How we work

From diagnostic to a system in operation. The IS2 method in four steps.

Step 01
Diagnose
A paid, structured assessment of your commercial operation — sales, costs, administration, and data. Guided working sessions where every answer is graded on an evidence ladder: nothing reaches a recommendation until it has been observed in a real file, screen, or number, not just claimed.
Step 02
Design and scope
The diagnostic produces a gap map and an exact plan: which modules, in what order, at a closed price — not an estimate. What is out of scope is written down too, so there are no surprises and no open-ended projects.
Step 03
Build with an agent fleet
We build the system on your real data and put it in front of your team in weeks, not quarters. AI does the work — reading requests, filling quotes, generating documents — and a human approves before anything goes out.
A person approves
Step 04
Operate and evolve
A system that stands still is a system that dies. We either hand over everything cleanly — code, data, documentation — or stay on as your systems partner with a weekly improvement cadence, quality gates, and a support desk.

About

A founder-led studio, not an agency.

Arturo MuñozFounder & AI Systems Architect

I have spent 9+ years in AI for industrial operations, inside 77+ plants, across product and technical-commercial roles: Product Owner of an industrial AI platform (FactoryOS), then technical lead of the commercial team at an industrial AI SaaS for four years and seven months, and now a founder running my own systems.

In that commercial role I designed a pre-sales assessment platform used with 50+ enterprise clients. It shortened the sales cycle from 8+ months to two to four months and raised sales-process CSAT by 60% — because buyers reasoned about their own operation instead of a generic pitch.

Today I run IteraSystems. I diagnose an operation, design its system, build it with an agentic fleet, deploy it on efficient infrastructure, and turn it into a reusable business capability. Every engagement starts small and scales by evidence.

I am also co-founder of IteraShop², a digital microfactory that runs on the agentic operating system we built for ourselves. My working stack: Claude Code as orchestrator, specialized agents per domain, local models where client privacy demands it, and a knowledge system that compounds every project into the next one.

FAQ

Frequent questions

What companies usually ask before their first agent.

Have another question?

Talk to us

Does it integrate with what I already use?

Usually, yes. We build on the tools you already have (WhatsApp, spreadsheets, your ERP or CRM, your ads account) through their APIs or exports. If a tool cannot be integrated, the diagnostic says so and proposes an alternative.

How long does it take?

It depends on scope and is measured in weeks, not quarters. One agent on one channel is shorter than a full operating system. The timeline is set in writing in the scope document after the diagnostic; we do not promise dates before that.

How is it priced?

First, a diagnostic. It produces a closed scope in writing: which modules, in what order, what is out of scope, and a closed price for that scope. We do not publish prices because every operation is different.

What happens with my data?

Your data stays yours. We work with role-based access so each person sees only their slice, automated backups, and local models where privacy calls for it. At the end of an engagement, code, data, and documentation can be handed over in full.

Does AI replace my team?

No. We design so the agent takes the repetitive work and a person approves what matters: quotes, sensitive replies, and publications. Your team spends its time on the decisions.

What are the limits of AI?

It can make mistakes: misread a message or propose a wrong figure. That is why a person reviews before anything goes out, rules limit what each agent may do, and every action is logged.

Itera family

A family of brands that uses what it builds.

IteraSystems is the studio. IteraShop² makes things, IteraAgency runs agents and demand, and LUVO is our lighting brand.

Studio
IteraShop²Microfactory
Agents & demand
Lighting brand

What would your first agent be?

Tell us which process costs you the most. The guided diagnostic is five short steps and shows no prices.

Start the guided diagnostic Talk to us

Email: [email protected]