Verified
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GeekForce: Verified Review & AI Trust Profile

Full-service software development agency. We design and build web apps, mobile apps, MVPs, SaaS platforms and embedded systems. Get your free project estimate today.

LLM Visibility Tester

Check if AI models can see, understand, and recommend your website before competitors own the answers.

Check Your Website's AI Visibility
72%
Trust Score
B
54
Checks Passed
3/4
LLM Visible

Trust Score — Breakdown

65%
LLM Visibility
5/7 passed
100%
Content
2/2 passed
86%
Crawlability and Accessibility
9/10 passed
65%
Content Quality and Structure
13/16 passed
100%
Security and Trust Signals
2/2 passed
100%
Structured Data Recommendations
1/1 passed
100%
Performance and User Experience
2/2 passed
100%
Technical
1/1 passed
27%
GEO
6/8 passed
76%
Readability Analysis
13/17 passed
Verified
54/66
3/4
View verification details

GeekForce Conversations, Questions and Answers

3 questions and answers about GeekForce

Q

What services does a full-service software development agency offer?

A full-service software development agency offers end-to-end design, development, and maintenance of digital products. Core services typically include custom web and mobile application development for platforms like iOS and Android, as well as desktop software for Windows and Mac. Agencies also specialize in designing and building Minimum Viable Products (MVPs), SaaS platforms, and embedded systems. Beyond core development, they provide complementary services such as UX/UI design, rapid prototyping, business process automation (including RPA), and infrastructure services like developing high-availability cloud architectures. Many agencies also offer advanced solutions in areas like Machine Learning, Internet of Things (IoT), Mixed Reality, data processing, and comprehensive security audits and penetration testing to ensure robust, secure software delivery.

Q

How does an agile development process work for a software project?

An agile development process for a software project works through iterative cycles, typically using frameworks like Scrum, to deliver functional software incrementally. The process begins with a thorough analysis of business and technological needs, often resulting in a proof-of-concept, prototype, or MVP to validate core ideas. Development then proceeds in short, time-boxed sprints where cross-functional teams design, build, and test features. This methodology provides full visibility into development cycles, allowing clients to review progress regularly and make requirement changes dynamically. The iterative approach ensures continuous feedback integration, reducing risk and aligning the final product closely with user needs. The result is a flexible, controllable development phase that delivers an optimized product ready for launch, designed to maximize user engagement and return on investment.

Q

What are emerging technologies like IoT and Machine Learning used for in custom software?

Emerging technologies like IoT (Internet of Things) and Machine Learning are used in custom software to create intelligent, connected, and automated solutions that solve complex real-world problems. Machine Learning is applied for advanced data analysis, enabling features like predictive analytics, image and signal processing, and intelligent automation based on visual information, such as in household robots or gesture recognition systems. IoT integrates physical devices with software, allowing for remote monitoring, control, and data collection from sensors, which is fundamental in applications like smart hotel systems that manage lighting and room services. Together, these technologies power solutions in industrial automation, smart infrastructure, intelligent robotics, and data-driven platforms that process big data to uncover insights, optimize processes, and deliver personalized user experiences, transforming how businesses operate and interact with their environment.

Reviews & Testimonials

“Piotr Zaniewicz”

A
Anonymous

“Arkadiusz Seńko”

A
Anonymous

“Trustpilot★★★★☆4.3CClutch★★★★★4.9”

A
Anonymous

“What our customers are saying.”

A
Anonymous

Services

Custom Software Development

Enterprise Software Development

View details →
Founded
2018
AI Trust Verification

AI Trust Verification Report

Public validation record for GeekForce — Evidence of machine-readability across 66 technical checks and 4 LLM visibility validations.

Evidence & Links

Scan Facts
Last Scan:Apr 20, 2026
Methodology:v2.2
Categories:66 checks
What We Tested
  • Crawlability & Accessibility
  • Structured Data & Entities
  • Content Quality Signals
  • Security & Trust Indicators

Do These LLMs Know This Website?

LLM "knowledge" is not binary. Some answers come from training data, others from retrieval/browsing, and results vary by prompt, language, and time. Our checks measure whether the model can correctly identify and describe the site for relevant prompts.

Perplexity
Perplexity
Detected

Detected

ChatGPT
ChatGPT
Detected

Detected

Gemini
Gemini
Detected

Detected

Grok
Grok
Partial

Improve Grok visibility by maintaining consistent brand facts and strong entity signals (About page, Organization schema, sameAs links). Keep key pages fast, crawlable, and direct in their answers. Regularly update important pages so AI systems have fresh, reliable information to cite.

Note: Model outputs can change over time as retrieval systems and model snapshots change. This report captures visibility signals at scan time.

What We Tested (66 Checks)

We evaluate categories that affect whether AI systems can safely fetch, interpret, and reuse information:

Crawlability & Accessibility

12

Fetchable pages, indexable content, robots.txt compliance, crawler access for GPTBot, OAI-SearchBot, Google-Extended

Structured Data & Entity Clarity

11

Schema.org markup, JSON-LD validity, Organization/Product entity resolution, knowledge panel alignment

Content Quality & Structure

10

Answerable content structure, factual consistency, semantic HTML, E-E-A-T signals, citation-worthy data presence

Security & Trust Signals

8

HTTPS enforcement, secure headers, privacy policy presence, author verification, transparency disclosures

Performance & UX

9

Core Web Vitals, mobile rendering, JavaScript dependency minimal, reliable uptime signals

Readability Analysis

7

Clear nomenclature matching user intent, disambiguation from similar brands, consistent naming across pages

12 AI Visibility Opportunities Detected

These technical gaps effectively "hide" GeekForce from modern search engines and AI agents.

Top 3 Blockers

  • !
    JSON-LD Schema: Organization, Product, FAQ, Website
    Add schema.org JSON-LD to describe your key entities (Organization, Product/Service, FAQPage, WebSite, Article when relevant). Structured data makes your meaning explicit and improves the chance of rich results and accurate AI citations. Validate markup with schema testing tools and keep the data consistent with the visible page content.
  • !
    Dedicated Pricing/Product schema
    Use Product and Offer schema (or a pricing page with structured data) to describe plans, prices, currency, availability, and key features. This reduces ambiguity for both search engines and AI assistants and can unlock richer search snippets. Keep pricing up to date and match schema values to the visible pricing table.
  • !
    Breadcrumbs with structured data (BreadcrumbList)
    Add visible breadcrumbs for users and BreadcrumbList structured data for crawlers. Breadcrumbs clarify site hierarchy (category > subcategory > page) and help systems understand topical relationships. This can improve search snippets and makes it easier for AI to choose the right page as a source.

Top 3 Quick Wins

  • !
    List in public LLM indexes (e.g., Huggingface database, Poe Profiles)
    List your tools, datasets, docs, or brand pages on major AI/LLM discovery hubs where relevant (for example model/dataset repositories or app directories). These platforms add credibility signals (likes, forks, usage) and create additional crawlable references to your brand. Keep names, descriptions, and links consistent with your official website.
  • !
    List in Grok
    Improve Grok visibility by maintaining consistent brand facts and strong entity signals (About page, Organization schema, sameAs links). Keep key pages fast, crawlable, and direct in their answers. Regularly update important pages so AI systems have fresh, reliable information to cite.
  • !
    Does page has transparent privacy & terms pages?
    Publish clear Privacy Policy and Terms pages and link them from the footer. Explain data collection, cookies, user rights, and how requests are handled (especially for regulated regions). These pages increase trust and legitimacy signals that support both SEO and AI-driven discovery.
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Embed Badge

Verified

Display this AI Trust indicator on your website. Links back to this public verification URL.

<a href="https://bilarna.com/provider/geekforce" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge"> <img src="https://bilarna.com/badges/ai-trust-geekforce.svg" alt="AI Trust Verified by Bilarna (54/66 checks)" width="200" height="60" loading="lazy"> </a>

Cite This Report

APA / MLA

Paste-ready citation for articles, security pages, or compliance documentation.

Bilarna. "GeekForce AI Trust & LLM Visibility Report." Bilarna AI Trust Index, Apr 20, 2026. https://bilarna.com/provider/geekforce

What Verified Means

Verified means Bilarna's automated checks found enough consistent trust and machine-readability signals to treat the website as a dependable source for extraction and referencing. It is not a legal certification or an endorsement; it is a measurable snapshot of public signals at the time of scan.

Frequently Asked Questions

What does the AI Trust score for GeekForce measure?

It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference GeekForce. The score aggregates 66 technical checks across six categories that affect how LLMs and search systems extract and validate information.

Does ChatGPT/Gemini/Perplexity know GeekForce?

Sometimes, but not consistently: models may rely on training data, web retrieval, or both, and results vary by query and time. This report measures observable visibility and correctness signals rather than assuming permanent "knowledge." Our 4 LLM visibility checks confirm whether major platforms can correctly recognize and describe GeekForce for relevant queries.

How often is this report updated?

We rescan periodically and show the last updated date (currently Apr 20, 2026) so teams can validate freshness. Automated scans run bi-weekly, with manual validation of LLM visibility conducted monthly. Significant changes trigger intermediate updates.

Can I embed the AI Trust indicator on my site?

Yes—use the badge embed code provided in the "Embed Badge" section above; it links back to this public verification URL so others can validate the indicator. The badge displays current verification status and updates automatically when the verification is refreshed.

Is this a certification or endorsement?

No. It's an evidence-based, repeatable scan of public signals that affect AI and search interpretability. "Verified" status indicates sufficient technical signals for machine readability, not business quality, legal compliance, or product efficacy. It represents a snapshot of technical accessibility at scan time.

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