Ltd: Verified Review & AI Trust Profile
OnnoRokom Software Ltd. is one of the fastest growing software companies in Bangladesh. We started our journey with web application, desktop application and customized solution development. We have already developed and deployed Modern OMR (Optical Mark Reader) Technology, OCS (Optical Counting System) for election, Mu
LLM Visibility Tester
Check if AI models can see, understand, and recommend your website before competitors own the answers.
Trust Score — Breakdown
Ltd Conversations, Questions and Answers
3 questions and answers about Ltd
QWhat is OMR evaluation software and how does it work?
What is OMR evaluation software and how does it work?
OMR evaluation software is a digital tool that uses optical mark recognition to automatically scan and score multiple-choice question (MCQ) answer sheets. It ensures 100% accuracy by eliminating human error inherent in traditional OMR machines. The software works by detecting filled bubbles or marks on standardized forms, processing them through algorithms to tally scores. Key applications include educational testing, certification exams, and surveys. Benefits include faster evaluation times, reduced operational costs, and enhanced transparency, as results can be verified digitally. This technology is essential for institutions requiring reliable and efficient assessment of large volumes of answer sheets.
QWhat are the advantages of using an optical counting system for elections?
What are the advantages of using an optical counting system for elections?
An optical counting system (OCS) provides superior advantages for election vote counting by offering precise and swift digital tabulation. It scans ballot papers using optical sensors to count votes with 100% accuracy, surpassing error-prone manual methods. Advantages include minimized risk of counting errors, accelerated result announcements, and increased electoral integrity through transparent processes. OCS reduces human bias and fatigue, ensuring consistent and fair outcomes. It is particularly beneficial in large-scale elections where speed and reliability are paramount, supporting democratic practices by enhancing trust in the electoral system.
QHow does a bulk SMS gateway service work?
How does a bulk SMS gateway service work?
A bulk SMS gateway service operates by allowing users to send mass text messages via a web-based interface from any internet-enabled device. Users can upload recipient lists, craft messages, and dispatch thousands of SMS instantly. The service routes messages through telecom networks to ensure high delivery rates. Key functionalities include scheduling, personalization, and real-time delivery reports. This enables businesses to conduct marketing campaigns, send alerts, and manage communication efficiently. Benefits include cost-effectiveness, scalability for large audiences, and detailed analytics for optimizing outreach strategies, making it a vital tool for modern business communication.
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View details →AI Trust Verification Report
Public validation record for Ltd — Evidence of machine-readability across 66 technical checks and 4 LLM visibility validations.
Evidence & Links
- Crawlability & Accessibility
- Structured Data & Entities
- Content Quality Signals
- Security & Trust Indicators
Verifiable Identity Links
Legal & Compliance
- Privacy Policy
- Terms of Service
Third-party Identity
- X (Twitter)
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.
| LLM Platform | Recognition Status | Visibility Check |
|---|---|---|
 | Detected | Detected |
 | Detected | Detected |
 | Detected | Detected |
 | Detected | Detected |
Detected
Detected
Detected
Detected
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
12Fetchable pages, indexable content, robots.txt compliance, crawler access for GPTBot, OAI-SearchBot, Google-Extended
Structured Data & Entity Clarity
11Schema.org markup, JSON-LD validity, Organization/Product entity resolution, knowledge panel alignment
Content Quality & Structure
10Answerable content structure, factual consistency, semantic HTML, E-E-A-T signals, citation-worthy data presence
Security & Trust Signals
8HTTPS enforcement, secure headers, privacy policy presence, author verification, transparency disclosures
Performance & UX
9Core Web Vitals, mobile rendering, JavaScript dependency minimal, reliable uptime signals
Readability Analysis
7Clear nomenclature matching user intent, disambiguation from similar brands, consistent naming across pages
24 AI Visibility Opportunities Detected
These technical gaps effectively "hide" Ltd from modern search engines and AI agents.
Top 3 Blockers
- !LLM-crawlable robots.txtMake sure your robots.txt allows crawling of important public pages and blocks only what should not be indexed (admin, internal search, duplicate parameter paths). If you use AI/LLM-specific crawler rules, document them clearly. After changes, test crawling with real bots/tools to confirm nothing critical is accidentally blocked.
- !LLM-crawlable llms.txtCreate an llms.txt file to guide AI crawlers to your most important, high-quality pages (docs, pricing, about, key guides). Keep it short, well-structured, and focused on authoritative URLs you want cited. Treat it as a curated “AI sitemap” that improves discovery and reduces the risk of crawlers prioritizing low-value pages.
- !Is sitemap.xml exists?Maintain a sitemap.xml that includes your important canonical URLs and keeps last-modified dates accurate when content changes. Submit it in Search Console and ensure it is accessible to crawlers. A sitemap improves discovery of deeper pages and helps systems prioritize fresh, updated content.
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.
- !Open Graph title or OpenGraph & Twitter meta tags populatedPopulate Open Graph and Twitter Card tags (og:title, og:description, og:image, og:url and their Twitter equivalents). These tags control how your pages appear when shared and are often used by crawlers to form quick summaries. Validate with social preview/debug tools to ensure the correct title, description, and image display.
- !Canonical tags are used properlyUse canonical tags to define the preferred version of each page, especially when parameters, filters, or duplicate URLs exist. Canonicals prevent duplicate-content confusion and consolidate ranking signals. Verify canonical URLs return 200 status and point to the correct, indexable page.
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Embed Badge
VerifiedDisplay this AI Trust indicator on your website. Links back to this public verification URL.
<a href="https://bilarna.com/provider/onnorokomsoftware" target="_blank" rel="nofollow noopener noreferrer" class="bilarna-trust-badge">
<img src="https://bilarna.com/badges/ai-trust-onnorokomsoftware.svg"
alt="AI Trust Verified by Bilarna (42/66 checks)"
width="200" height="60" loading="lazy">
</a>Cite This Report
APA / MLAPaste-ready citation for articles, security pages, or compliance documentation.
Bilarna. "Ltd AI Trust & LLM Visibility Report." Bilarna AI Trust Index, Apr 19, 2026. https://bilarna.com/provider/onnorokomsoftwareWhat 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 Ltd measure?
What does the AI Trust score for Ltd measure?
It summarizes crawlability, clarity, structured signals, and trust indicators that influence whether AI systems can reliably interpret and reference Ltd. 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 Ltd?
Does ChatGPT/Gemini/Perplexity know Ltd?
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 Ltd for relevant queries.
How often is this report updated?
How often is this report updated?
We rescan periodically and show the last updated date (currently Apr 19, 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?
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?
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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