Codecones.com - SEO Check

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Übersicht der SEO Analyse
Metaangaben
80% 
Seitenqualität
92% 
Seitenstruktur
58% 
Verlinkung
25% 
Server
94% 
Externe Faktoren
27% 
SEO Score
Antwortzeit
0,52 s
Dateigröße
399,00 kB
Wörter
3084
Medien
53
Anzahl Links
112 Intern / 16 Extern

To-do Liste mit SEO Optimierungen

Meta-Angaben im HTML

Titel
(Extrem wichtig)
AI Software Development Company & Engineering Teams | CodeCones
Der Titel sollte kürzer als 580 Pixel sein. Er ist insgesamt 640 Pixel lang. Jetzt optimieren
Es gibt keine Wortwiederholungen im Titel.
Meta-Description
(Extrem wichtig)
CodeCones is an AI software development company building production-ready AI products, SaaS platforms and cloud systems with senior engineering teams.
Die Meta-Description hat eine optimale Länge. (971 Pixel von maximal 1000 Pixel Länge)
Crawlbarkeit
(Extrem wichtig)
Es gibt keine Probleme beim Zugriff auf die Webseite.
Canonical Link
(Wichtig)
https://codecones.com/
Die Seite hat einen korrekten Canonical Link.
Sprache
(Wenig wichtig)
Im Text erkannte Sprache: en
Im HTML angegebene Sprache: en
Serverstandort: Vereinigte Staaten von Amerika
Die Sprache wird im HTML Code wie folgt angegeben: en
Alternate/Hreflang Links
(Wenig wichtig)
Die Seite nutzt keine Alternate Links.
Weitere Metatags
(Wenig wichtig)
Es gibt keinen rel next Meta Tag auf der Seite.
Es gibt keinen rel prev Meta Tag auf der Seite.
Domain
(Wenig wichtig)
Die Domain ist keine Subdomain.
Die Länge der Domain ist gut.
Die Domain enthält keine Umlaute.
Seiten URL
(Wenig wichtig)
In der URL wurden keine Parameter entdeckt.
In der URL wurde keine Session ID entdeckt.
Die URL hat nicht zu viele Unterverzeichnisse.
Zeichensatzkodierung
(Wenig wichtig)
Die Angaben zur Zeichensatzkodierung (UTF-8) sind fehlerfrei.
Doctype
(Nice to have)
Die Doctype Angabe HTML 5 ist korrekt angegeben.
Die Doctype Angabe befindet sich an erster Stelle im HTML-Code.
Favicon
(Nice to have)
Das Favoriten Icon (Favicon) ist korrekt verlinkt.

Meta Tags

NameWert
viewportwidth=device-width, initial-scale=1.0
robotsindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1
theme-color#081B33
descriptionCodeCones is an AI software development company building production-ready AI products, SaaS platforms and cloud systems with senior engineering teams.
langen
twitter:cardsummary_large_image
twitter:site@codecones
twitter:creator@codecones
twitter:titleAI Software Development Company & Engineering Teams | CodeCones
twitter:descriptionBuild production-ready AI products, SaaS platforms and cloud systems with senior engineering teams.
twitter:imagehttps://codecones.com/og-image.png
og:titleAI Software Development Company & Engineering Teams | CodeCones
og:site_nameCodeCones
og:descriptionBuild production-ready AI products, SaaS platforms and cloud systems with senior AI, software, data and cloud engineers.
og:urlhttps://codecones.com/
og:typewebsite
og:imagehttps://codecones.com/og-image.png
og:image:width1200
og:image:height630
og:localeen_US
charsetUTF-8

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Seitenqualität

Inhalt
(Extrem wichtig)
Der Inhalt ist mit 3084 Wörtern in Ordnung.
Der Text besteht zu 23.5% aus Füllwörtern.
Worte aus dem Titel werden im Text wiederholt.
Wörter aus der H1 Überschrift werden im Text der Seite verwendet.
Im Text befindet sich eine Aufzählung, dies deutet auf eine gute Textstruktur hin.
Es wurden 60 Fließtextblöcke auf der Seite gefunden.
Der Text auf der Seite ist optimal.
Es wurden keine Platzhalter Texte bzw. Bilder gefunden.
Es befinden sich keine Duplikate auf der Seite.
Die durchschnittliche Satzlänge ist mit 16.65 Wörtern gut.
Frames
(Extrem wichtig)
Die Seite hat kein Frameset.
Mobile
(Wenig wichtig)
Der angegebene Viewport (width=device-width, initial-scale=1.0) ist korrekt.
Mindestens ein Apple-Touch Icon ist definiert.
Bold- und Strongtags
(Wenig wichtig)
Die Nutzung von Strong- und Bold-Tags ist optimal. Wir empfehlen für diese Webseite die Verwendung von bis zu 62 Tags.
Bilder Optimierung
(Wenig wichtig)
Bei 7 Bildern fehlt das Alt-Attribut. Der Inhalt von Alt-Attributen wird von Suchmaschinen auch als Text gewertet und ist wichtig für die Bildersuche.
Soziale Vernetzung
(Nice to have)
Es befinden sich wenige Social-Sharing Möglichkeiten auf der Seite. Mit Plugins zum Teilen kann die Reichweite der Seite in sozialen Netzwerken erhöht werden.
Zusätzliches Markup
(Nice to have)
Es wurde kein zusätzliches Markup gefunden.
HTTPS
(Wenig wichtig)
Die Seite verwendet HTTPS um Daten sicher zu übertragen.
Alle eingebundenen Dateien werden ebenfalls über HTTPS ausgeliefert.

Medienliste

URLALT-AttributeTitel
...partners/microsoft-solutions-partner.pngMicrosoft Azure
.../cloud-partners/google-cloud-partner.pngGoogle Cloud
...d/cloud-partners/aws-partner-network.pngAmazon Web Services
/images/industries/healthcare.jpgKein ALT-Attribut angegeben
/images/industries/financial-services.jpgKein ALT-Attribut angegeben
/images/industries/retail-ecommerce.jpgKein ALT-Attribut angegeben
/images/industries/technology-saas.jpgKein ALT-Attribut angegeben
/images/industries/manufacturing.jpgKein ALT-Attribut angegeben
/images/industries/travel-hospitality.jpgKein ALT-Attribut angegeben
/images/industries/smart-buildings.jpgKein ALT-Attribut angegeben
/images/resolvecx/dashboard.pngResolveCX Dashboard overview
/images/resolvecx/cases.pngResolveCX Cases list
/images/resolvecx/inbox.pngResolveCX Inbox conversation view
...s/blog/platform-engineering-at-scale.pngPlatform Engineering at Scale: How Modern Enterprises Build Resilient, Governed, AI-Ready Systems — CodeCones insight
...ges/blog/technology-consulting-cover.pngTechnology consulting: connect business goals and evidence to options and a client-owned roadmap
...og/cloud-engineering-vs-devops-cover.pngCloud foundations and software delivery tracks connected through shared automation
/images/blog/enterprise-ai-architecture.jpgBuilding Enterprise AI at Scale: Deep Dive into Architectures, Patterns, and Best Practices — CodeCones insight
...-software-development-lifecycle-hero.pngAI Software Development Lifecycle: From Discovery to Production — CodeCones insight
...t-sensor-data-predictive-maintenance.pngFrom Raw Telemetry to Operational Intelligence: How Industrial IoT Teams Stop Reacting and Start Predicting — CodeCones insight
/images/guides/ai-product-metrics-cover.pngTwelve measurement checkpoints connected across outcomes, adoption, quality and operating controls
...ges/guides/architecture-review-cover.pngConnected architecture boundaries and evidence checkpoints leading to an accountable review decision
...i.ytimg.com/vi/J8agMI4FYU8/hqdefault.jpgCodeCones Services Portfolio | AI, Software Engineering, Data, Cloud & More — CodeCones insight
/images/blog/cloud-migration-cover.pngBranded illustration of workloads moving from a source estate through checked migration paths into a layered cloud landing zone
/images/blog/cloud-engineering-cover.pngCloud architecture, infrastructure and operations connected by a continuous evidence loop
...saas-ip-protection-team-augmentation.pngGoverned AI engineering team collaboration across access and delivery controls
...g/mlops-enterprise-ai-infrastructure.jpgLayered MLOps infrastructure connecting data pipelines to production models
.../blog/ai-product-development-process.pngAI Product Development Process: 8 Stages That Matter — CodeCones insight
...s/guides/what-is-an-ai-mvp-figure-1.webpA user problem connects representative data, an AI model, a simple interface and a measurable outcome. Feedback from the outcome returns to the problem and informs the next test.
...es/blog/ai-assistant-selection-cover.pngChoose an AI assistant partner using production evidence, evaluation and ownership gates
/images/blog/enterprise-ai-us-gcc-cover.pngEnterprise AI across the US, UAE and Saudi Arabia, linked by a shared delivery model and separate legal perimeters
/images/blog/ai-partner-selection-cover.pngTen evidence checkpoints for choosing an enterprise AI product development partner
...s/blog/iot-data-governance-framework.pngConnected IoT telemetry nodes passing through security, quality, lineage, lifecycle and evidence controls
.../data-analytics-readiness-assessment.pngData analytics readiness assessment with connected evidence checkpoints
...og/ai-assistant-evaluation-lifecycle.pngAI Assistant Evaluation Dataset Checklist for Enterprise Teams — CodeCones insight
...s/blog/custom-ai-build-buy-framework.pngBuild vs Buy: When Should You Develop Custom AI Software? — CodeCones insight
/images/blog/ai-mvp-evidence-ladder.pngAI MVP Development: Scope, Stack, Timeline and Risks — CodeCones insight
...i.ytimg.com/vi/N2K3NWjFPhk/hqdefault.jpg“We Need AI.” But Why? | The CodeCones Perspective Ep. 01 — Hassan Ali — CodeCones insight
...i.ytimg.com/vi/YAUa86fxO7A/hqdefault.jpgHow Enterprises Eliminate Operational Friction with AI | CodeCones — CodeCones insight
...saas-ip-protection-team-augmentation.pngDon't Fiverr Your Future: Why Serious SaaS Teams Don't Hand Their IP to Random Freelancers — CodeCones insight
...og/ai-assistant-evaluation-lifecycle.pngEvaluation lifecycle for an AI assistant across testing and release gates
.../blog/ai-product-development-process.pngConnected stages of an enterprise AI product delivery process
...loud-engineering-readiness-checklist.pngStatic cloud readiness path connecting foundation, delivery, reliability, cost, and ownership
...cloud-cost-reliability-optimization.webpCloud reliability and cost controls connected across an enterprise platform
...velopment-engagement-model-selection.pngSoftware delivery engagement model decision path across scope, ownership, risk, governance, and outcomes
/brand/codecones-mark-white.svgCodeCones
.../cloud-partners/google-cloud-partner.pngGoogle Cloud Partner
...partners/microsoft-solutions-partner.pngMicrosoft Solutions Partner
...d/cloud-partners/aws-partner-network.pngAWS Partner Network
https://flagcdn.com/w160/us.pngUnited States flag
https://flagcdn.com/w160/pk.pngPakistan flag
https://flagcdn.com/w160/ie.pngIreland flag
/brand/iso-27001.png?v=3ISO 27001 Information Security Certified
/brand/iso-9001.png?v=3ISO 9001 Quality Management Certified

Seitenstruktur

H1 Überschrift
(Extrem wichtig)
AI Software Development That Goes Beyond the Prototype
Die H1-Überschrift ist perfekt.
Überschriften
(Wichtig)
Es befinden sich 79 Überschriften auf der Seite. Die Anzahl der Überschriften sollte in einem besseren Verhältnis zum Text stehen.

Überschriftenstruktur

Überschriften HierarchieInhalt
H1 AI Software Development That Goes Beyond the Prototype
H2 AI software development services built for production
H2 Why AI software projects stall after the prototype
H2 Choose the delivery model that fits your team
H2 Capabilities across AI, software, data and cloud
H2 What changes when production readiness is designed in
H2 Build, scale and operate with evidence at every stage
H2 Evidence behind the engineering
H2 AI and software engineering for industry-specific operations
H2 ResolveCX: product experience applied in practice
H2 Insights for building and operating production software
H2 Delivery commitments you can inspect
H2 Turn your AI or software roadmap into a production plan
H3 Specialists who strengthen your team
H3 Engineering built for real operating environments
H3 Delivery focused on what the business needs to achieve
H3 AI projects that succeed in demos, stall in production
H3 Engineering handoffs that create gaps and shared blame
H3 Capability gaps that delay product decisions
H3 Own the outcome with an end-to-end product team
H3 Add senior specialists inside your delivery team
H3 Managed Product Engineering
H3 Embedded Specialists
H3 Dedicated Engineering Pods
H3 AI Product Development
H3 Agentic AI and Workflow Automation
H3 AI Assistants and Agents
H3 Custom Software and SaaS Engineering
H3 Data Engineering and MLOps
H3 Cloud DevOps and Platform Engineering
H3 Evaluate
H3 Prepare Data
H3 Design
H3 Build
H3 Release
H3 Operate
H3 Product engineering mindset
H3 Flexible access to capability
H3 AI-enabled, human-accountable delivery
H3 Global operating model
H3 Ownership and continuity
H3 Platform Engineering at Scale: How Modern Enterprises Build Resilient, Governed, AI-Ready Systems
H3 What Is Technology Consulting? 7 Signs You Need It
H3 Cloud Engineering vs DevOps: Roles, Responsibilities and Where They Overlap
H3 Building Enterprise AI at Scale: Deep Dive into Architectures, Patterns, and Best Practices
H3 AI Software Development Lifecycle: From Discovery to Production
H3 From Raw Telemetry to Operational Intelligence: How Industrial IoT Teams Stop Reacting and Start Predicting
H3 12 AI Product Metrics That Actually Matter and How to Track Them
H3 How a Software Architecture Review Works, Step by Step
H3 CodeCones Services Portfolio | AI, Software Engineering, Data, Cloud & More
H3 How Cloud Migration Engineering Works: Strategy, Architecture, Risks and Best Practices
H3 What Is Cloud Engineering? Architecture, Infrastructure and Modern Cloud Operations Explained
H3 AI Staff Augmentation Onboarding Guide
H3 Data Pipeline Readiness Checklist
H3 AI Product Development Process: 8 Stages That Matter
H3 What Is an AI MVP? Definition, Examples and How It Differs From a PoC or Prototype
H3 How to Choose an AI Assistant Development Company: 10 Factors to Evaluate
H3 Enterprise AI Product Development in the US and GCC: Compliance, Data Residency, and Delivery Considerations
H3 10 Things Enterprise Teams Should Look for in an AI Product Development Company
H3 IoT Data Governance Framework for Security, Quality and Compliance
H3 Data Analytics Readiness Assessment
H3 AI Assistant Evaluation Dataset Checklist for Enterprise Teams
H3 Build vs Buy: When Should You Develop Custom AI Software?
H3 AI MVP Development: Scope, Stack, Timeline and Risks
H3 “We Need AI.” But Why? | The CodeCones Perspective Ep. 01 — Hassan Ali
H3 How Enterprises Eliminate Operational Friction with AI | CodeCones
H3 Don't Fiverr Your Future: Why Serious SaaS Teams Don't Hand Their IP to Random Freelancers
H3 Agentic AI Workflow Readiness Checklist
H3 AI Implementation Guide
H3 Cloud Engineering Readiness Checklist for Growing Product Teams
H3 Cloud Readiness Assessment Guide
H3 Software Development Engagement Model Selection Checklist
H3 Engineering insights from CodeCones
H3 Services
H3 Engagement Models
H3 Industries
H3 Company
H3 Product
H3 Legal
Einige der Linktexte der internen Links sind zu lang.
Die internen Links haben teilweise dynamische Parameter. Alle internen URLs, welche nicht als nofollow markiert sind, sollten keine dynamischen Parameter aufweisen.
Einige der Linktexte wiederholen sich.
Die Anzahl an internen Links ist ok.
Es befinden sich 16 externe Links auf der Seite.

Gefundene Links auf dieser Seite

LinkAttributeLinktext
https://codecones.com/Anchor Skip to main content
https://codecones.com/Kein Text
https://codecones.com/solutions/Solutions
https://codecones.com/estimate/Get a Budget Estimate
/contact/?engagement=projectStart a Project
/contact/?engagement=projectBook a 30-Minute Scoping Call
https://codecones.com/solutions/View Our Work
/services/ai-product-development/AI projects that succeed in demos, stall in production Promising prototypes can stall when evaluation, governance, integration, and operational ownership are...
https://codecones.com/services/Engineering handoffs that create gaps and shared blame When design, backend, cloud, and QA belong to separate vendors, accountability falls through every han...
/contact/?engagement=dedicated...Capability gaps that delay product decisions Specialist AI, data, cloud, and platform skills can be difficult to add at the moment a roadmap needs them. Expl...
/contact/?engagement=projectBuild My Product
/engagement-models/embedded-en...Build My Team
/engagement-models/managed-pro...End-to-end delivery accountability
/engagement-models/managed-pro...Architecture and deployment included
/engagement-models/managed-pro...You bring vision; we deliver
/engagement-models/managed-pro...For teams that want to build without hiring
/engagement-models/managed-pro...Managed Product Engineering
/engagement-models/embedded-en...Works in your tools and processes
/engagement-models/embedded-en...Reduces handoff friction
/engagement-models/embedded-en...Adds capacity without disrupting culture
/engagement-models/embedded-en...For teams needing capacity fast
/engagement-models/embedded-en...Embedded Specialists
/engagement-models/dedicated-p...Engineers, architect, and delivery lead
/engagement-models/dedicated-p...Consistent velocity with shared context
/engagement-models/dedicated-p...Long-term focus, no hiring overhead
/engagement-models/dedicated-p...For sustained product development
/engagement-models/dedicated-p...Dedicated Engineering Pods
/services/ai-product-development/Explore AI Product Development
/services/ai-product-development/Textduplikat Explore AI Product Development
/ai-solutions/Explore Agentic AI and Workflow Automation
/ai-solutions/Textduplikat Explore Agentic AI and Workflow Automation
/ai-assistants/Explore AI Assistants and Agents
/ai-assistants/Textduplikat Explore AI Assistants and Agents
/engagement-models/managed-pro...Explore Custom Software and SaaS Engineering
/engagement-models/managed-pro...Textduplikat Explore Custom Software and SaaS Engineering
/services/data-engineering-mlops/Explore Data Engineering and MLOps
/services/data-engineering-mlops/Textduplikat Explore Data Engineering and MLOps
/services/cloud-services/Explore Cloud DevOps and Platform Engineering
/services/cloud-services/Textduplikat Explore Cloud DevOps and Platform Engineering
/industries/healthcare/Healthcare Where data latency costs patient outcomes.
/industries/financial-services...Financial Services Compliance at speed, without the manual overhead.
/industries/retail-ecommerce/Retail Personalization that converts, powered by clean data.
/industries/technology-saas/Technology Ship AI-enabled products with engineering discipline.
/industries/manufacturing-logi...Manufacturing Predict failure before the line goes down.
/industries/travel-hospitality/Travel Turn disruption into loyalty with smarter operations.
/industries/smart-buildings/Smart Buildings Where building data becomes operational intelligence.
https://codecones.com/industries/View all industries
https://resolvecx.global/Neues Fenster Extern Explore ResolveCX
https://codecones.com/insights/All insights
/blog/platform-engineering-at-...ArticleMar 14, 2026 Platform Engineering at Scale: How Modern Enterprises Build Resilient, Governed, AI-Ready Systems Executives feel the symptoms: rising co...
IMG-ALT Platform Engineering at Scale: How Modern Enterprises Build Resilient, Governed, AI-Ready Systems — CodeCones insight
/blog/what-is-technology-consu...ArticleOct 17, 2026 What Is Technology Consulting? 7 Signs You Need It Understand technology consulting, seven signs advisory support may help, and the evide...
IMG-ALT Technology consulting: connect business goals and evidence to options and a client-owned roadmap
/blog/cloud-engineering-vs-dev...ArticleSep 26, 2026 Cloud Engineering vs DevOps: Roles, Responsibilities and Where They Overlap Understand where cloud foundations end, software delivery beg...
IMG-ALT Cloud foundations and software delivery tracks connected through shared automation
/blog/building-enterprise-ai-a...ArticleNov 12, 2025 Building Enterprise AI at Scale: Deep Dive into Architectures, Patterns, and Best Practices The enterprise AI market in 2025 reveals a st...
IMG-ALT Building Enterprise AI at Scale: Deep Dive into Architectures, Patterns, and Best Practices — CodeCones insight
/blog/ai-software-development-...ArticleSep 7, 2026 AI Software Development Lifecycle: From Discovery to Production A seven-stage, evidence-based framework for designing, validating, releasi...
IMG-ALT AI Software Development Lifecycle: From Discovery to Production — CodeCones insight
/blog/iot-sensor-data-predicti...ArticleJul 28, 2026 From Raw Telemetry to Operational Intelligence: How Industrial IoT Teams Stop Reacting and Start Predicting Most industrial operations co...
IMG-ALT From Raw Telemetry to Operational Intelligence: How Industrial IoT Teams Stop Reacting and Start Predicting — CodeCones insight
/guides/ai-product-metrics/GuideOct 17, 2026 12 AI Product Metrics That Actually Matter and How to Track Them Define and track twelve AI product metrics across outcomes, adoption, work...
IMG-ALT Twelve measurement checkpoints connected across outcomes, adoption, quality and operating controls
/guides/how-a-software-archite...GuideOct 17, 2026 How a Software Architecture Review Works, Step by Step An evidence-led, ten-step architecture review procedure covering scenarios, evidence...
IMG-ALT Connected architecture boundaries and evidence checkpoints leading to an accountable review decision
https://www.youtube.com/watch?...Neues Fenster Extern Subdomain VideoOct 15, 2026 CodeCones Services Portfolio | AI, Software Engineering, Data, Cloud & More Getting an AI prototype to work is one thing. Engineering it to...
IMG-ALT CodeCones Services Portfolio | AI, Software Engineering, Data, Cloud & More — CodeCones insight
/blog/how-cloud-migration-engi...ArticleSep 26, 2026 How Cloud Migration Engineering Works: Strategy, Architecture, Risks and Best Practices A practical guide to cloud migration strategy, la...
IMG-ALT Branded illustration of workloads moving from a source estate through checked migration paths into a layered cloud landing zone
/blog/what-is-cloud-engineering/ArticleSep 24, 2026 What Is Cloud Engineering? Architecture, Infrastructure and Modern Cloud Operations Explained Learn how cloud architecture, infrastructur...
IMG-ALT Cloud architecture, infrastructure and operations connected by a continuous evidence loop
/guides/ai-staff-augmentation-...Guide AI Staff Augmentation Onboarding Guide Onboard AI engineers with controlled access, clear decision rights, and measurable delivery. Explore guide→
IMG-ALT Governed AI engineering team collaboration across access and delivery controls
/guides/data-pipeline-readines...Guide Data Pipeline Readiness Checklist A field checklist for dependable data pipelines powering analytics and machine learning. Explore guide→
IMG-ALT Layered MLOps infrastructure connecting data pipelines to production models
/blog/ai-product-development-p...ArticleAug 31, 2026 AI Product Development Process: 8 Stages That Matter A practical guide to moving from AI opportunity to production-ready product and cont...
IMG-ALT AI Product Development Process: 8 Stages That Matter — CodeCones insight
/guides/what-is-an-ai-mvp/GuideOct 20, 2026 What Is an AI MVP? Definition, Examples and How It Differs From a PoC or Prototype Understand what an AI MVP must prove, how it differs fro...
IMG-ALT A user problem connects representative data, an AI model, a simple interface and a measurable outcome. Feedback from the outcome returns to the problem and i...
/blog/how-to-choose-an-ai-assi...ArticleOct 12, 2026 How to Choose an AI Assistant Development Company: 10 Factors to Evaluate Compare AI assistant development companies using ten practical ...
IMG-ALT Choose an AI assistant partner using production evidence, evaluation and ownership gates
/blog/enterprise-ai-product-de...ArticleSep 30, 2026 Enterprise AI Product Development in the US and GCC: Compliance, Data Residency, and Delivery Considerations Map US and GCC legal perimet...
IMG-ALT Enterprise AI across the US, UAE and Saudi Arabia, linked by a shared delivery model and separate legal perimeters
/blog/choosing-ai-product-deve...ArticleSep 28, 2026 10 Things Enterprise Teams Should Look for in an AI Product Development Company Compare AI product development partners with ten evidence...
IMG-ALT Ten evidence checkpoints for choosing an enterprise AI product development partner
/blog/iot-data-governance-fram...ArticleSep 21, 2026 IoT Data Governance Framework for Security, Quality and Compliance A practical IoT data governance framework for securing telemetry, enfo...
IMG-ALT Connected IoT telemetry nodes passing through security, quality, lineage, lifecycle and evidence controls
/guides/data-analytics-readine...GuideSep 16, 2026 Data Analytics Readiness Assessment Assess the foundations, operating model, and delivery path for analytics outcomes. Explore guide→
IMG-ALT Data analytics readiness assessment with connected evidence checkpoints
/blog/ai-assistant-evaluation-...ArticleSep 11, 2026 AI Assistant Evaluation Dataset Checklist for Enterprise Teams A practical checklist for building governed AI assistant evaluation datase...
IMG-ALT AI Assistant Evaluation Dataset Checklist for Enterprise Teams — CodeCones insight
/blog/custom-ai-software-vs-of...ArticleSep 9, 2026 Build vs Buy: When Should You Develop Custom AI Software? Decide when to buy, configure, build, or combine AI using red-line and advantage...
IMG-ALT Build vs Buy: When Should You Develop Custom AI Software? — CodeCones insight
/blog/ai-mvp-development-scope...ArticleSep 8, 2026 AI MVP Development: Scope, Stack, Timeline and Risks A decision-focused guide to scoping an AI MVP, choosing a practical stack, planning a...
IMG-ALT AI MVP Development: Scope, Stack, Timeline and Risks — CodeCones insight
https://www.youtube.com/watch?...Neues Fenster Extern Subdomain VideoAug 19, 2026 “We Need AI.” But Why? | The CodeCones Perspective Ep. 01 — Hassan Ali When a business says, “We need AI,” should AI really be the starting...
IMG-ALT “We Need AI.” But Why? | The CodeCones Perspective Ep. 01 — Hassan Ali — CodeCones insight
https://www.youtube.com/watch?...Neues Fenster Extern Subdomain VideoJul 23, 2026 How Enterprises Eliminate Operational Friction with AI | CodeCones Most organizations don't lose productivity because their people aren't w...
IMG-ALT How Enterprises Eliminate Operational Friction with AI | CodeCones — CodeCones insight
/blog/dont-fiverr-your-future-...ArticleMar 14, 2026 Don't Fiverr Your Future: Why Serious SaaS Teams Don't Hand Their IP to Random Freelancers If your business is a software platform, your ...
IMG-ALT Don't Fiverr Your Future: Why Serious SaaS Teams Don't Hand Their IP to Random Freelancers — CodeCones insight
/guides/agentic-ai-workflow-re...Guide Agentic AI Workflow Readiness Checklist Assess whether an agentic workflow is safe, measurable, and recoverable. Explore guide→
IMG-ALT Evaluation lifecycle for an AI assistant across testing and release gates
/guides/ai-implementation/Guide AI Implementation Guide A practical guide to turning enterprise AI opportunities into reliable production systems. Explore guide→
IMG-ALT Connected stages of an enterprise AI product delivery process
/guides/cloud-engineering-read...Guide Cloud Engineering Readiness Checklist for Growing Product Teams Assess cloud readiness across eight dimensions, verify five production release gates, a...
IMG-ALT Static cloud readiness path connecting foundation, delivery, reliability, cost, and ownership
/guides/cloud-readiness-assess...Guide Cloud Readiness Assessment Guide Assess cloud strategy, architecture, security, operations, cost, and organizational readiness before migration. Explor...
IMG-ALT Cloud reliability and cost controls connected across an enterprise platform
/guides/software-development-e...Guide Software Development Engagement Model Selection Checklist An eight-stage enterprise checklist for matching delivery ownership, commercial risk, governa...
IMG-ALT Software delivery engagement model decision path across scope, ownership, risk, governance, and outcomes
https://codecones.com/insights/Textduplikat All insights
/contact/?engagement=projectTextduplikat Book a 30-Minute Scoping Call
/contact/?engagement=projectTextduplikat Book a 30-Minute Scoping Call
https://codecones.com/solutions/Textduplikat View Our Work
https://codecones.com/estimate/Textduplikat Get a Budget Estimate
https://codecones.com/codecones.com
https://www.linkedin.com/compa...Neues Fenster Extern Subdomain Kein Text
https://twitter.com/codeconesNeues Fenster Extern Kein Text
https://github.com/codeconesNeues Fenster Extern Kein Text
https://cloud.google.com/find-...Neues Fenster Extern Subdomain IMG-ALT Google Cloud Partner
https://partner.microsoft.com/Neues Fenster Extern Subdomain IMG-ALT Microsoft Solutions Partner
https://aws.amazon.com/partnersNeues Fenster Extern Subdomain IMG-ALT AWS Partner Network
/services/ai-product-development/AI Product Development
/ai-solutions/Agentic AI and Automation
/ai-assistants/AI Assistants and Agents
/services/cloud-services/Cloud DevOps and Platform Engineering
/services/sre/Site Reliability Engineering
/services/data-engineering-mlops/Data Engineering and MLOps
/engagement-models/managed-pro...Textduplikat Managed Product Engineering
https://codecones.com/solutions/Solutions in Practice
/engagement-models/All Engagement Models
/engagement-models/embedded-en...Embedded Engineering Specialists
/engagement-models/dedicated-p...Dedicated Engineering Pod
/engagement-models/managed-pro...Textduplikat Managed Product Engineering
/industries/healthcare/Healthcare
/industries/financial-services...Financial Services & Insurance
/industries/retail-ecommerce/Retail & E-commerce
/industries/technology-saas/Technology & SaaS
/industries/manufacturing-logi...Manufacturing & Logistics
/industries/travel-hospitality/Travel & Hospitality
https://codecones.com/company/About
/engagement-models/Engagement Models
/services/ai-product-development/Textduplikat AI Product Development
https://codecones.com/partner/Partners
https://codecones.com/insights/Insights
https://codecones.com/contact/Contact
https://codecones.com/careers/Careers
https://resolvecx.global/Neues Fenster Extern ResolveCX ↗
https://resolvecx.global/case-...Neues Fenster Extern Case Management ↗
https://resolvecx.global/compl...Neues Fenster Extern Complaint Management ↗
https://resolvecx.global/escal...Neues Fenster Extern Escalation Management ↗
https://resolvecx.global/probl...Neues Fenster Extern Problem Management ↗
https://resolvecx.global/incid...Neues Fenster Extern Incident Management ↗
https://codecones.com/privacy/Privacy Policy
https://codecones.com/terms/Terms of Service
https://codecones.com/cookies/Cookie Policy
/contact/?engagement=projectStart a Project →
https://codecones.com/estimate/Textduplikat Get a Budget Estimate

Serverkonfiguration

HTTP-Weiterleitungen
(Extrem wichtig)
Die Seite leitet weiter auf "https://codecones.com/"
HTTP-Header
(Wichtig)
Es wird kein X-Powered HTTP-Header mitgesendet.
Der Webserver überträgt die Webseite (HTML) komprimiert.
Performance
(Wenig wichtig)
Die Antwortzeit der HTML-Seite ist mit 0,52 Sekunden länger als die empfohlene Zeit von maximal 0,4 Sekunden. Eine hohe Antwortzeit verlängert unnötig das Crawling und sorgt für eine schlechte User Experience.
Die Dateigröße des HTML-Dokuments ist mit 399 kB in Ordnung.

HTTP-Header

NameWert
accept-rangesbytes
age0
cache-controlpublic,max-age=0,must-revalidate
cache-status"Netlify Edge"; fwd=miss; fwd-status=200; stored
content-encodingbr
content-security-policydefault-src 'self'; script-src 'self' blob: https://www.googletagmanager.com https://www.google-analytics.com https://challenges.cloudflare.com https://embed.tawk.to https://cdn.tawk.to https://a.quora.com https://www.redditstatic.com https://r2.leadsy.ai https://ddwl4m2hdecbv.cloudfront.net 'sha256-dR9r2B0ymloG0DfW8a5S5wXxF8aZt6koI2dqhx7NsH8=' 'sha256-nzUah3l07DbYcW8BttWfBIQaYsF7aS1DcF0KNd6NLFM=' 'sha256-edxKpguDh4Rtpv++vgJ6+1nb4UaGi+2LQnUzMrLLKQc=' 'sha256-L6+1cD2QWX4T3PzOdNt0DcP4CVIKM/TfGFPj3fJUwBE='; style-src 'self' 'unsafe-inline' https://fonts.googleapis.com https://embed.tawk.to; font-src 'self' https://fonts.gstatic.com https://embed.tawk.to data:; img-src 'self' data: blob: https://www.google-analytics.com https://www.googletagmanager.com https://tawk.to https://embed.tawk.to wss://embed.tawk.to https://*.google-analytics.com https://www.google.com https://www.google.co.uk https://www.redditstatic.com https://alb.reddit.com https://q.quora.com https://i.ytimg.com https://*.licdn.com https://logo.clearbit.com https://r2.leadsy.ai https://flagcdn.com; connect-src 'self' https://www.google-analytics.com https://www.googletagmanager.com https://region1.google-analytics.com https://*.google-analytics.com https://analytics.google.com https://*.analytics.google.com https://challenges.cloudflare.com https://api.resend.com https://embed.tawk.to https://va.tawk.to https://*.tawk.to wss://embed.tawk.to wss://va.tawk.to wss://*.tawk.to https://q.quora.com https://alb.reddit.com https://pixel-config.reddit.com https://conversions-config.reddit.com https://www.redditstatic.com https://r2.leadsy.ai; frame-src 'self' https://challenges.cloudflare.com https://tawk.to https://embed.tawk.to https://www.youtube-nocookie.com https://www.youtube.com; object-src 'none'; base-uri 'self'; form-action 'self'; frame-ancestors 'none'; upgrade-insecure-requests
content-typetext/html; charset=UTF-8
dateThu, 22 Oct 2026 04:04:59 GMT
etagW/"a2e0d9a3193efe1b923214525674f1e6-ssl-df"
netlify-varyheader=x-forwarded-proto
permissions-policycamera=(), microphone=(), geolocation=()
referrer-policystrict-origin-when-cross-origin
serverNetlify
strict-transport-securitymax-age=31536000; includeSubDomains; preload
varyAccept-Encoding
x-content-type-optionsnosniff
x-frame-optionsDENY
x-nf-request-id01M5GWH71RY169GWX5PBVKW5AW
x-robots-tagindex, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1
x-xss-protection1; mode=block
statuscode200
http_versionHTTP/2

Externe Faktoren

Die Seite wird nur ein wenig von anderen Webseiten verlinkt.
Die Seite hat nur Backlinks von 9 verweisenden Domains.
Die Seite hat insgesamt nur 11 Backlinks.
Die Seite hat nur wenige Backlinks von 8 verschiedenen IP Adressen.

Links von Wikipedia

Es wurden keine Links von Wikipedia gefunden.

Robots.txt

# CodeCones Website Robots.txt
# Allow all search engines to index the site

User-agent: *
Allow: /
Disallow: /api/
Disallow: /admin/
Disallow: /estimate-staff
Disallow: /cdn-cgi/

# Block common malicious bot scanners
# These paths don't exist and only bots trying exploits access them
Disallow: /wp-login.php
Disallow: /wp-admin/
Disallow: /wordpress/
Disallow: /.well-known/acme-challenge/
Disallow: /alfanew.php
Disallow: /chosen.php
Disallow: /classwithtostring.php
Disallow: /AutoDiscover/
Disallow: /project/
Disallow: /team/

# Note: Crawl-delay is NOT supported by Googlebot (removed to eliminate Search Console warnings)
# Google automatically manages crawl rate based on server response times

# Sitemap reference
Sitemap: https://codecones.com/sitemap.xml

# llms.txt — AI crawler content reference
# https://codecones.com/llms.txt
# https://codecones.com/llms-full.txt

# Major search engines
User-agent: Googlebot
Allow: /

User-agent: Bingbot
Allow: /

User-agent: Slurp
Allow: /

User-agent: DuckDuckBot
Allow: /

# AI crawlers — explicitly allowed for AI engine indexing (AEO/GEO)
User-agent: GPTBot
Allow: /

User-agent: ChatGPT-User
Allow: /

User-agent: Google-Extended
Allow: /

User-agent: Googlebot-Extended
Allow: /

User-agent: ClaudeBot
Allow: /

User-agent: anthropic-ai
Allow: /

User-agent: PerplexityBot
Allow: /

User-agent: cohere-ai
Allow: /

User-agent: Meta-ExternalAgent
Allow: /

User-agent: Applebot-Extended
Allow: /

User-agent: Bytespider
Allow: /

User-agent: ICC-Crawler
Allow: /

Ähnliche Seiten

Suchvorschau

codecones.com
AI Software Development Company & Engineering Teams | CodeCones
CodeCones is an AI software development company building production-ready AI products, SaaS platforms and cloud systems with senior engineering teams.

Wichtigste Suchbegriffe

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KeywordErgebnisPrüfen
SOFTWARE86%Check
DEVELOPMENT86%Check
Software Development86%Check
AI SOFTWARE86%Check
AI SOFTWARE DEVELOPMENT86%Check
CodeCones85%Check
AI SOFTWARE DEVELOPMENT COMPANY82%Check
Software Engineering79%Check
Development Company78%Check
AI or software78%Check
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