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Mirlo Systems

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Production AI Systems for Mid-Market Operators

Mirlo Systems is a specialist AI agency that designs, builds, and operates production-grade AI systems and workflow automation for established mid-market and enterprise businesses worldwide. The firm delivers eight core services: AI Voice Agents, Workflow Automation, AI Customer Support, AI Sales and Marketing, AI Reporting and Analytics, Internal Knowledge AI, Custom AI Development, and AI Strategy and Advisory. Every engagement follows a disciplined three-stage, six-phase delivery model with formal client sign-off required at every phase before work moves forward. No pilots. No off-the-shelf tools. Production-ready AI built for real operational load. Serving the US, UK, Canada, Australia, UAE, Saudi Arabia, Germany, France, Netherlands, Ireland, and worldwide.

  • Min project size
    $25,000+
  • Hourly rate
    $150 - $199 / hr
  • Employees
    50 - 249
  • Year founded
    Founded 2026

Service Lines
AI Development
50%
Custom Software Development
20%
Business Consulting
15%
IT Managed Services
15%
Select Focus Area
AI Expertise
Chatbots & Conversational AI
25%
Voice and Speech Recognition
25%
Machine Learning
15%
Natural Language Processing
15%
Computer Vision
10%
AI Recommendation Systems
5%
Cognitive Computing
5%
Application Platforms
Amazon Application Development Framework
40%
Azure Platform
35%
Google app engine
25%
AI Technologies & Models
Anthropic
50%
Cohere
20%
Hugging Face Bloom
20%
Open AI GPT-3
10%
Business Consulting Focus
Strategy Development Consulting
40%
Business Transformation Consulting
30%
Business Intelligence Consulting
20%
Business Process Management Consulting
10%
Frameworks and CMS
React
40%
NextJS
30%
NodeJS
20%
Django
10%
IT Managed Services Focus
Managed Software Application & Solutions
40%
Cloud Server Migration
30%
Governance & Compliance Assessments
20%
Software Evaluation
10%
Programming & Scripting
Python
40%
JavaScript
30%
Typescript
15%
SQL
10%
Go
5%
Industries
Business services
25%
Information technology
20%
Financial services
15%
Medical
15%
Real estate
10%
Supply Chain, Logistics, and Transport
10%
Hospitality & leisure
5%
Clients
Midmarket ($10M - $1B)
50%
Enterprise (>$1B)
40%
Small Business (<$10M)
10%

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Our Story

Mirlo Systems was built on one belief: most AI implementations fail not because the technology does not work, but because the implementation is rushed and disconnected from real operational needs. We partner with mid-market and enterprise operators to build production-grade AI systems that survive real operational load. Six-phase delivery. Formal sign-off at every stage. No pilots. No demos.

What Sets Us Apart

Six-Phase Delivery With Formal Sign-Off

Every engagement runs through six signed-off phases before go-live. Formal client approval is required at every stage. No phase starts until the previous one is signed off. This eliminates the 75% pilot failure rate that plagues most AI implementations.

Full Code Ownership Transferred at Go-Live

Every system we build belongs to the client. Full source code, documentation, admin access, and architecture diagrams are handed over at go-live. No vendor lock-in. No ongoing dependency on Mirlo Systems to keep the lights on.

Integrated Into Your Existing Stack

We build AI that fits into what you already run. Every system integrates directly with your existing CRM, ERP, telephony, and databases. No forced platform switch. No ripping out working infrastructure. AI that slots into real operations from day one.

Commonly Asked Questions

Every Mirlo Systems engagement begins with a paid Discovery and Diagnosis phase. We conduct stakeholder interviews, map existing processes, audit your current tech stack, and identify where AI creates the most measurable leverage. A written Discovery Report covering current state, proposed solution, scope boundaries, timeline, and cost is delivered and requires client sign-off before any build work begins. This phase typically takes 1-2 weeks and ensures both parties are fully aligned before a single line of code is written.

Project timelines depend on scope and complexity. A focused AI voice agent deployment typically runs 6-8 weeks from discovery to go-live. A multi-system workflow automation or enterprise RAG implementation typically runs 10-14 weeks. Every timeline is defined during the Design and Architecture phase and agreed in writing before build starts. We do not give estimates without a completed discovery. Timelines are protected by our six-phase model which catches scope and technical issues before they become delays.

ROI varies by engagement type. Our hospitality clients have recovered six-figure OTA commission losses through direct booking automation. Our logistics clients have eliminated dispatcher hours wasted on status queries the TMS already had the answers to. Our healthcare clients have recovered seven-figure annual losses from appointment no-shows and uncaptured recall patients. Every engagement defines measurable success metrics during the design phase and tests against them before go-live. We do not launch systems that have not met their agreed performance benchmarks.

Every client has a named point of contact for the full duration of the engagement. During the build phase we run weekly check-ins and provide milestone updates at each signed-off phase. We build in a staging environment and give clients access to review the system before go-live. After launch we provide a monthly performance report covering volume, accuracy, and optimization actions taken. There is no generic support inbox and no account manager who does not understand the technical side of the build.

Every Mirlo Systems build is tested against success metrics defined and agreed during the Design and Architecture phase. Structured QA, edge-case testing, and client user acceptance testing are all required before go-live. If a system does not meet the agreed benchmarks, resolution happens inside the same engagement before cutover. Formal client sign-off is a required gate before go-live, not an optional review. This staging-first, sign-off-gated process is designed to catch and correct performance gaps before a system ever reaches production traffic.

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