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PILLAR IV — CONTINUOUS CALIBRATION

Your AI works perfectly today. What about in 6 months?

Eighty percent of enterprise AI projects fail in the first 90 days due to lack of maintenance. Audit and Continuous Calibration keeps your system at optimal performance month after month, without you having to worry about it.

Request a free audit of your current AI
Key metric

< 1%

target error rate

Key metric

30 min/mes

only 30 minutes from your team; the rest is on us

Key metric

Improves

the system improves every month instead of degrading

Your AI works perfectly today. What about in 6 months?
CONTROL PANEL
Premium architecture for executive control
Operational control with full traceability
European infrastructure ready for growth
Human oversight in every critical decision

The AI installed 6 months ago no longer works the same. Nobody knows why.

Silent degradation

The first week the system works perfectly. Months pass, documents and processes change, and the system keeps answering with old references. Performance declines without a clear signal until the failure becomes visible.

Failures nobody analyzes and that keep repeating

Many AI projects degrade between month 3 and month 12 not because of bad initial implementation, but because nobody maintains them. When that happens, the company keeps paying for a system that answers worse every week.

The provider that disappears after delivery

When nobody continuously calibrates the system, a late recovery ends up costing more than the monthly maintenance that was avoided.

The calibration team working on your system while you work on your business

Audit and Continuous Calibration is the monthly active maintenance service that keeps any enterprise AI system at optimal performance. It works with AuroraCortex systems or with any third-party system that allows access to logs and configuration.

  • Monthly analysis of logs and detected incorrect answers

  • Correction and recalibration of the responsible agent or prompt

  • Policy and knowledge-base updates

  • Monthly executive report with metrics, corrected failures, and applied improvements

  • 30-minute monthly review meeting with your team

  • Compatible with AuroraCortex systems or third-party systems

INDUSTRY DATA

Gartner and McKinsey converge on one key idea: most enterprise AI failures do not come from the initial installation, but from the lack of active maintenance, knowledge updates, and continuous calibration. The conclusion is simple: an AI system is not a project. It is a living service that requires active care.

Source: Gartner / McKinsey 2024
🧠 SIX SIGMA APPLIED TO AI: PRECISION MEASURED, NOT PROMISED

Six Sigma sets an objective of extreme defect reduction. Applied to enterprise AI, we set a pragmatic target: less than 1% error rate in responses and actions. We measure it with three metrics: error rate, detection time, and correction time. These metrics are reported every month. They are not estimates. They are data.

Real scenarios

COMPANY WITH KNOWLEDGE CORTEX · 50–200 EMPLOYEES
Four months after deployment, the team was reporting strange answers. Usage had dropped by 40%.

Internal documents had been updated, processes had changed, and the system kept answering with obsolete references. The team stopped trusting it.

Implementation: 3-week audit, full recalibration, and monthly maintenance plan.

Usage recovered to 90% of peak in 3 weeks. The audit identified 127 outdated documents and 14 poorly calibrated prompts.

COMPANY WITH THIRD-PARTY AI · 100–500 EMPLOYEES
Maintenance was on demand and never happened. The system had significantly degraded.

They had contracted an AI system from another provider. Post-sales maintenance was reactive and late. The system silently degraded for 8 months.

Implementation: Technical audit plus monthly maintenance plan on the third-party system.

Performance recovered to 85% in 6 weeks. Savings versus replacing the system: €45,000.

Active maintenance cycle

Before kickoff
Phase 1
Baseline audit

We audit the system’s current state: existing failures, outdated knowledge, poorly calibrated prompts, and real performance level.

Month 1
Phase 2
Month 1 — inherited fixes

We correct the problems identified in the baseline audit to restore the system to optimal level.

Weeks 1–2
Phase 3
Weeks 1–2 — analysis and correction

We review logs, classify error patterns, and apply calibration corrections.

Weeks 3–4
Phase 4
Weeks 3–4 — update and report

We update the knowledge base and deliver the monthly report with the review meeting.

Investment and return

Indicative pricing by number of AI systems. The exact price is defined in the initial technical audit.

1 system
Setup

€800

Monthly
€450/month

Maintenance of 1 AI system

Full monthly cycle

30-minute monthly meeting

Urgent SLA: response <2h / resolution <24h

6-month minimum

>3 systems
Setup

Contact us

Monthly
From €1,200/month

More than 3 AI systems

Pricing by number of systems and complexity

Contract-defined SLA

Dedicated engineering

Custom integrations

Indicative prices are non-binding. The final figure is confirmed after a free technical audit.

Frequently asked questions

Does the service work with AI systems installed by other providers?

What access do you need to maintain the system?

How much time from my team does the service require each month?

What happens if there is a critical failure between monthly reviews?

Does it include system updates when new base model versions appear?

Can I cancel the service without penalty?

NEXT MOVE

Is your AI working today as well as the day it was installed?

If the answer is no or I do not know, the free 1-hour audit tells us the real condition of the system and what it needs to get back to 100%. No commitment. No cost.

Talk to an architect →
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