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AI Visibility Scorecard
steffi.ai · Technology
Somewhat visible. AI bots can read Olib AI, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 5 times
Claude · Amazon Alexa · Apple Intelligence
#311,192 of 2,641,478 in Technology for AI visibility
5.8
/10
AEO Score
from our crawl and measurement
Olib AI is a business whose own site puts it this way: "Building secure autonomous AI agent infrastructure for business operations." To AI engines like ChatGPT and Perplexity it is partially visible, scoring 5.7 out of 10, readable in places and missing in others.
Our crawl found structured data on the page (WebSite, Organization, SoftwareApplication), an llms.txt file for AI models and a sitemap.
AI crawlers have visited 5 times in our tracking, including ClaudeBot (Anthropic), AmazonBot (Alexa AI) and Applebot (Siri).
Higher is better · 0-10
Structured Data
8
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
10
Clear headings and answer-style content.
Entity Clarity
6
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
4
Experience, Expertise, Authority, Trust markers.
Technical AEO
10
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
8
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
7
Inbound links from other sites.
Domain Authority
0
Little domain authority yet.
Reference Presence
0
Not in AI knowledge graphs yet.
News & Press
0
No press coverage found yet.
Community
0
No community discussion yet.
Social Mentions
0
No social discussion found yet.
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 5.8/10, Olib AI has a working base to build on - fixable, and the signals above are where to start.
What is steffi.ai?
steffi.ai is an autonomous AI agent platform built in Rust. It deploys long-running AI agents that reason, plan, use tools, and make decisions for hours or days — not seconds. Agents operate as persistent workers with identity, memory, tools, budgets, and oversight. The platform ships as a single Rust binary with Docker-ready deployment.
How is steffi.ai different from other AI agent frameworks?
steffi.ai is built entirely in Rust for performance and safety. Unlike Python-based frameworks, orchestration logic runs in compiled Rust — not in LLM calls — resulting in 5x fewer tokens per task. It features a 4-tier persistent memory system, multi-agent council deliberation, 6-layer prompt injection defense, and enterprise governance with SOC 2 controls. The LLM is a component inside the system, not the system itself.
What plugins does steffi.ai support?
steffi.ai includes 19 production plugins: Browser automation (CEF + Chrome CDP via Owl Browser), email (SMTP/IMAP), Slack, Mattermost, sandboxed Python and Node.js execution, file manager, Git, Google Drive, HTTP templates/requests, webhooks, RAG (Retrieval Augmented Generation), object store, OCR helpers, HubSpot, Salesforce, Intercom, Zendesk, and hardware IO.
How does steffi.ai handle AI agent security?
steffi.ai implements 6-layer prompt injection defense covering role hijack, instruction override, context manipulation, data exfiltration, recursive injection, and credential exfiltration. It also features AES-256-GCM encrypted credential vault, capability-gated permissions, DLP output filtering, immutable audit logs with chain hashing, and resource budgets per agent and task.
Can steffi.ai agents run for long periods?
Yes. steffi.ai agents are designed for long-running autonomy — operating for hours or days continuously. They use Erlang-OTP style supervision trees, circuit breakers per LLM provider, behavioral loop detection, and an emergency kill switch. The 4-tier persistent memory system ensures agents retain context and build expertise over time.
What is multi-agent orchestration in steffi.ai?
steffi.ai supports multi-agent council deliberation with four modes: Brainstorm (collaborative idea synthesis), Debate (advocate and judge pattern), Review (producer with critics), and Consensus (iterative agreement). Agents can also decompose work into DAG task graphs with parallel and sequential execution, cascade cancellation, and depth limits.
Is steffi.ai built for financial and healthcare compliance?
Yes. steffi.ai is built from the ground up to support regulated enterprises. It includes native support for SOC 2 controls, AES-256-GCM encrypted credential vaults, immutable chain-hashed audit logs, and pattern-based DLP (Data Loss Prevention) filtering, which are critical for HIPAA and PCI-DSS compliance audits.
What use cases can steffi.ai automate?
steffi.ai is used across 12 primary verticals: Financial Services (KYC/AML), Healthcare Operations, Enterprise IT & SecOps, Customer Support Automation (Zendesk/Intercom), Sales & CRM Operations, Large-Scale Web Research (Owl Browser integration), Legal & Document Processing, DevOps & Infrastructure, Manufacturing & IoT, Data Engineering Pipelines, HR & Employee Onboarding, and Supply Chain & Logistics.
Is this your brand?
The exact fixes for Olib AI
Which AI engines already crawl you
Weekly ChatGPT & Claude citation tracking
The search landscape has fundamentally shifted. While Google still dominates, millions of users now ask questions to ChatGPT, Gemini, and Claude instead of typing into a search bar.
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Scored by Engagemii on August 1, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/steffi-ai
Cite this score: Engagemii (2026). "AEO Score for Olib AI." Retrieved from https://engagemii.com/aeo/brands/steffi-ai
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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