When your website, automation, or AI setup breaks — we triage it, stabilize it, and rebuild it properly.
Independent repair & recovery for business operators — broken websites, stalled n8n / Make / Zapier flows, misbehaving AI tools, damaged spreadsheets. We respond fast to assess what broke, put a stopgap in place, capture evidence of what actually happened, and hand back a system you and your team can supervise — not a black box.
Request an urgent assessment →B2B service for businesses and operators only. We respond quickly to initial inquiries — we do not promise a specific fix time or outcome before we’ve seen your system.
Does this sound familiar?
Most teams don’t notice their automation has failed until it has already cost them something. If two or more of these are true right now, it’s worth a second set of eyes before the gap gets wider.
None of these mean the project was a failure on your part. Pilots and integrations break for ordinary, common reasons — a connector update, an undocumented edge case, a model change upstream, scope that grew past what was governed. The fix starts with an honest look at what’s actually happening today.
Reviewing the tools you already have
Recovery is not always about fixing. Sometimes it is about taking honest stock:
- We check the current state of the AI tools and automations you already installed.
- We sort out what stopped working, what is unused, and what has grown too complex to maintain.
- Where useful, we propose what to keep and what to retire.
Depending on your vendor contracts, admin permissions, and backups, some things may be outside what we can touch. We tell you clearly at the diagnosis stage what we can and cannot do — and if something is not worth fixing, we say so and do not start.
Our response flow
Four stages, in order. We don’t skip to a rebuild before we know what’s actually broken, and we don’t leave a stopgap running unsupervised indefinitely.
Triage
Fast initial review of what’s running, what’s failing, and what’s actually at risk right now — data, customer-facing output, or downstream systems.
Stopgap fix
Contain the immediate damage — pause, isolate, or hand-guard the failing step — so the business keeps running while the real cause is investigated.
Evidence capture
Record what the system actually did — logs, run history, decision points — so you have a real account of impact, not guesswork, if you need to explain it to a customer, partner, or regulator.
Prevention rebuild
Rebuild the workflow with checkpoints, recorded decisions, and clear human sign-off points so the same failure mode is far less likely to recur unnoticed.
Why this doesn’t just break again
Every rebuild is governed by the same four principles we apply across all of our AI work. They’re not a slogan — they’re the actual checkpoints built into how the system runs afterward.
Staged review
Work passes through multiple checkpoints rather than running end-to-end unsupervised. Each stage is reviewed before the next begins.
Stop when uncertain
If approval, a record, or consistency is missing at any point, the process halts automatically rather than guessing and continuing.
Tamper-evident records
What the system did is logged in a way designed to surface tampering or gaps, not just a feel-good activity log.
Humans decide what matters
Payment, contractual commitments, final pricing, and other decisions you designate as significant stay with a named person — not the automation.
This same discipline — staged review, recordkeeping, and stop-when-uncertain checkpoints — comes from prior back-office audit work in a compliance-sensitive sector, applied here to AI and automation systems.
What we don’t promise: a guaranteed fix, a guaranteed timeline, or a guaranteed outcome before we’ve assessed your specific system. Some failures are quick to stabilize; others reveal a deeper rebuild is needed. We will tell you honestly which situation you’re in once we’ve looked, and we won’t claim a result we haven’t verified.
Built to keep running, not just to stop safely
Beyond the rebuild itself, we can design ongoing monitoring into the system so the next failure is caught early.
| 1 | A monitoring bot detects the anomaly and first attempts an automatic repair for known, common failure patterns. |
| 2 | If it can’t self-repair, it signals a person rather than guessing and continuing on its own. |
| 3 | While that’s being handled, the setup can optionally fail over to a lightweight Google Apps Script (GAS) fallback so the business isn’t left fully offline. |
| 4 | Every step carries a trace identifier, so we can pinpoint exactly which stage or integration caused the issue and dispatch a targeted remote fix. |
This is not a guarantee of zero downtime — it’s a design pattern for noticing problems fast, deciding deliberately, and keeping the business running with minimal disruption while a fix is in progress. Scope and what’s auto-repairable is designed per system.
Pricing guide
We diagnose first, agree the scope, then quote. Every estimate itemizes exactly what diagnosis, repair, and maintenance include.
| Repair & recovery (one-off) | $1,000 – $3,000 typical range (quoted after diagnosis) |
| Small fixes (a single broken layout, one stuck flow) | Individually quoted |
| Post-repair maintenance | $100 – $300 / month (scope agreed together) |
| On-site visits (nationwide Japan) | $300 per day ($500 for complex work), plus actual travel and accommodation costs. Most work is completed remotely. |
Initial consultation is free. We do not guarantee that everything can be fixed — we tell you honestly at diagnosis.
If your AI or automation has stopped behaving, don’t wait for it to get worse.
Tell us what’s running and what’s gone wrong. We’ll get back to you quickly with an honest read on whether this is a quick stabilization or a deeper rebuild — see our pricing page for current service tiers.
Request an urgent assessment →MIRAI AI ORCHESTRA — independent, single-operator AI implementation and governance consulting for business operators. B2B only.
For larger recovery, redesign, or full operations work, please use the email contact on this page.
