From pieces to production.

INTO builds production AI for businesses. A fixed-fee discovery, then working software in two-week sprints. You own everything.

Every vendor claims AI now.

The demos impress. The proof never reaches the operation. From the outside, a deck-seller and a builder look identical.

So this page doesn't pitch. It runs.

Standing still is a decision with a cost.

The proof

One business. One day. In production.

Five systems run a fictional company's day, on data you can change. Watch the hours land — or take the controls.

Fictional data. Conversations aren't stored.

  1. 07:00

    Anticipate

    The 7 a.m. brief

    Anticipate: Generate this morning's brief.

    money at risk > customer promise > staffing > efficiency

    1. Laval returns hit $6,200 yesterday — 3× the $2,050 trailing average.

      sales.laval-returns

    2. PEX ½in is out at Montréal — $3,800 of committed orders can't ship.

      stock.pex-out

    3. Plomberie Delisle escalated a $22,000 order running two days late.

      escalation.delisle

    4. Three shipments worth $9,400 slipped past their promise window.

      orders.late-shipments

    5. One counter clerk called in sick at Laval; the desk is covered.

      staffing.laval-sick

    Nothing else needs your attention.

    Ranked by the rubric on the left. Every line cited. Silence earned, not assumed.

    Anticipate: 8 sick calls in Calgary

    money at risk > customer promise > staffing > efficiency

    1. Laval returns hit $6,200 yesterday — 3× the $2,050 trailing average.

      sales.laval-returns

    2. PEX ½in is out at Montréal — $3,800 of committed orders can't ship.

      stock.pex-out

    3. Plomberie Delisle escalated a $22,000 order running two days late.

      escalation.delisle

    4. Three shipments worth $9,400 slipped past their promise window.

      orders.late-shipments

    5. new since 7:00Calgary: 8 sick calls overnight — the counter can't open on time.

      staffing.calgary

    Applied: 8 sick calls in Calgary. The brief re-ranked.

    Nord & Fils — plumbing-supplies distributor, 3 branches

    1. Read
    2. Reason
    3. Route
    4. Measure
    Open the full demo →
  2. 09:15

    Act

    The invoice that filed itself

    Act: Clean invoice — matches PO

    Extracted fields with per-field confidence
    VendorLaurentide Tubes Inc.98%
    Invoice #LT-8823199%
    POPO-104297%
    Quantity4096%
    Unit price$15.0095%
    Total$600.0099%
    • PASSPO required over $500 — $600.00 invoice · PO-1042 on file
    • PASSPrice variance ±3% — $15.00 vs $15.00 on PO-1042 (0.0%)
    • PASSNet-30 approved vendors only — Laurentide Tubes Inc. — approved, net-30

    Filed

    Extracted, validated, filed. No human needed — by design, for this one.

    Act: Mismatch — price over variance

    Extracted fields with per-field confidence
    VendorFournitures Boréal98%
    Invoice #FB-220199%
    POPO-104497%
    Quantity6096%
    Unit price$14.8595%
    Total$891.0099%
    • PASSPO required over $500 — $891.00 invoice · PO-1044 on file
    • HOLDPrice variance ±3% — $14.85 vs $13.75 on PO-1044 (+8.0%)
    • PASSNet-30 approved vendors only — Fournitures Boréal — approved, net-30

    Draft for approval

    Over the variance rule, so a human approves. The rule decided, not the mood.

  3. 11:00

    Synthesize

    The Monday question

    Synthesize: Are we on track for August 15?

    The permit is the critical path: blocked: permit pending (filed Jul 8) · permit review 5-7 business days from Jul 15 · needs the panel decision by Jul 21 · scheduled (Groupe Comptoir, Aug 2). Tight, but August 15 holds if the permit lands this week.

    board.plumbingmessages.citymessages.electricianboard.counters

    One question. Four sources. Cited.

    Synthesize: Can I afford the quartz upgrade?

    $7,500 contingency − $4,200 quartz = $3,300 — but electrical is already $2,400 over. Doable, thin. Flagging both.

    budget.contingencybudget.countersbudget.electrical

    Math shown, risk named.

    Café Saint-Denis — renovation, opening Aug 15

    1. Read
    2. Reason
    3. Route
    4. Measure
    Open the full demo →
  4. 15:40

    Answer

    The guest who asks everything

    Answer: What's the wifi password?

    Wifi: LOFT402 / bienvenue2026.

    manual.wifi

    Answered from the manual. Nothing invented.

    Answer: The bathroom sink is leaking.

    This needs a person. I've alerted the operator — unit, your message, and the building super's on-call status attached.

    manual.super

    Damage, safety, money: a human owns it. Every time.

  5. 23:47

    Speak

    The 11:47 PM call

    Speak: Play the call

    1. 11:47 PM

      systemIncoming call — guest at the keypad.

      avaLe 402, this is Ava. How can I help?

      guestHi — I just got in, it's late, and the door won't open.

    2. 11:47 PM

      guestDésolé — mon français est plus simple là. Le code ne rentre pas.

      avaAucun souci, je continue en français. On regarde ça ensemble.

    3. 11:48 PM

      avaI've re-sent your entry code to your phone — the same one from check-in. You're booked through checkout at 11:00, so settle in — no rush in the morning.

      guestGot it — the code worked. Thank you.

    She matched the guest's language, mid-call. Loi 96, handled.

The model is the easy part.

Production lives in the system around it: permissions, source data, integrations, rules, monitoring, and a clear line between what AI may do and what a person must decide.

See it work →

Every system ships with

  • Sources you control
  • Rules you can inspect
  • A human hand-off
  • A trail you can audit

That was fictional. The next band isn't.

The bar is production.

Not slideware. Not a demo. Systems that run every day.

~75%

of guest responses handled autonomously, in our own operation

12 months

from first sprint to a production platform, with Operto

20,000+

candidate profiles matched in minutes

Fair questions

Ask us anything we can prove.

The same kind of system we sell, pointed at ourselves. Answers come from the sources beside it, cited. When a question needs judgment, you get a person.

Answers come only from the sources shown. Conversations aren't stored.

Fair questions. The answers should be clear before the call.
What if AI isn't ready for our use case?
Then the answer is no, and you'll know in two weeks for $20,000 instead of a year from now for much more. The go/no-go exists so you find out cheaply. We have told clients no.
Who owns what you build?
You do. The IP, the data, the prompts, the systems. If we part ways, everything keeps running and everything stays with you.
What does delivery cost after discovery?
It's scoped in your SOW and billed by sprint. Discovery exists so that number is grounded in your operation, not a brochure.
How fast is Phase 1?
First production release in sprints, not quarters. A full platform takes longer; we co-built Operto's over twelve months of sprints.
What about Quebec's Law 25?
Every workflow we ship is designed human-in-the-loop: automated decisions are disclosed, reviewable, and reversible. We host in Canada when compliance demands it.
Do you train models on our data?
No. Your data stays yours, full stop.
Do you work in French?
Yes, natively. Customer-facing software used in Québec must work in French; everything we build is bilingual by default.

What $20,000 buys.

Two weeks to replace ambiguity with a build decision.

Week 1

Read the operation.

We sit inside your operation. We read the workflows, the tickets, the spreadsheets, and we find the work AI should own.

Week 2

Design the system.

We design the system, scope the build, and price it.

  • Your data stays yours. We don't train models on it.

  • Your systems run without us. Documentation is part of done.

  • Cancel anytime. We earn the next sprint or we don't.

Canada-hosted when compliance demands it.

AI use by Canadian businesses: 6.1% actual in 2024, 19.2% actual in 2026, and a 60% federal target for 2034.

Adoption tripled in two years.

AI use by Canadian businesses rose from 6.1% to 19.2% in two years. Canada has now set a 60% business-adoption target for 2034.

Statistics Canada, Q2 2026Government of Canada, AI for All

The next honest step takes two weeks.

Book a discovery call