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Technical Policies

Last updated: October 21, 2026

Practical rules for people, bots, crawlers, AI systems, agents, and client software touching Hypler systems.

1. Purpose and Scope

These Technical Policies explain how Hypler expects public visitors, clients, vendors, crawlers, AI systems, and software agents to interact with Hypler websites, demos, public content, private systems, and project environments. They support our Privacy Policy and Terms of Service.

This page is a public operational baseline. Signed statements of work, security addenda, data processing terms, nondisclosure agreements, or written client instructions control when they conflict with this page.

2. Public AI and Agent Access

Hypler permits open automated access to its public content. Search engines, answer engines, AI crawlers, accessibility tools and research agents may read, index, retrieve and cache complete public pages. Hypler-authored public text may also be used for AI training, fine-tuning and evaluation, including commercial AI systems, without registration or a separate access agreement.

  • Use robots.txt for crawl rules, llms.txt for discovery, and the sitemap and Markdown exports for content. Honor cache headers, canonical URLs, rate limits and any private-path exclusions.
  • Full-text retrieval, caching and AI datasets are permitted for Hypler-authored public text. Preserve canonical links, source dates, attribution and development status in source records; cite Hypler when presenting retrieved content.
  • Identify automated traffic when practical and use a real contact path for crawler questions or removal requests.
  • Avoid private, admin, account, vendor, payment, API write, authentication, staging, or non-public project environments unless Hypler explicitly authorizes access.
  • Stop or reduce traffic when blocked, challenged, rate-limited, or asked to pause.

3. Disallowed Automated Activity

  • Credential guessing, password spraying, session abuse, token probing, or attempts to bypass access controls.
  • Form spam, lead scraping, comment spam, fake appointments, fake accounts, or automated social engineering.
  • Denial-of-service behavior, cache busting, recursive crawling traps or excessive parallel requests that impair service. Use conditional requests and cached copies when practical.
  • The public-text permission does not license third-party articles, images, logos or trademarks, private data, unpublished material, source code or site designs. Their separate rights and licenses still apply.
  • Trying to infer client names, private project details, infrastructure, secrets, pricing, or non-public operational data.
  • Prompt injection, data exfiltration, tool abuse, or agent activity designed to make Hypler or a client system violate its rules.

4. AI-Assisted Services

Hypler may use AI tools, local models, hosted models, code assistants, search systems, workflow agents, and agent telemetry systems to support planning, drafting, summarization, software development, review, and quality checks.

  • Human review remains required before high-risk output becomes a final business, legal, financial, medical, security, safety, employment, customer-impacting, or production decision.
  • AI-assisted work should preserve source context, approval gates, audit trails, rollback paths, and clear ownership when the risk justifies it.
  • Client confidential data, trade secrets, credentials, regulated data, and private customer data should be minimized before AI processing.
  • Hypler does not intentionally use private client data to train public AI models unless the client gives written permission.
  • Project-specific AI providers, subprocessors, retention rules, and approval paths should be named in the project scope when needed.

5. Cookies, Logs, and Telemetry

Hypler may use cookies, local storage, session storage, analytics events, server logs, error logs, uptime checks, security telemetry, and similar technologies to operate and improve public and project systems.

  • Essential storage supports routing, security, forms, preferences, session behavior, and basic site functionality.
  • Analytics and performance data help us understand page usage, regional interest, errors, speed, and service demand.
  • Security logs help detect abuse, automated attacks, unauthorized access, spam, suspicious traffic, and system failures.
  • Where legally required and technically practical, Hypler honors applicable opt-out signals, including Global Privacy Control for sale or sharing signals.
  • Blocking cookies or storage may change how forms, preferences, analytics, embedded tools, or demos behave.

6. Security Testing and Responsible Disclosure

Do not run vulnerability scans, exploit attempts, load tests, credential tests, data extraction tests, or invasive security research against Hypler systems without written authorization. Good-faith reports are welcome when they avoid harm.

  • Report suspected vulnerabilities to contact@hypler.com with enough detail to reproduce and assess the issue.
  • Do not access, modify, delete, retain, or disclose data that is not yours.
  • Do not maintain persistence, pivot to other systems, disrupt service, or publish details before Hypler has reviewed the report.
  • Hypler may ask for additional information, apply temporary mitigations, or restrict traffic while investigating.

7. Data Handling and Retention

Hypler applies data minimization, least privilege, limited retention, source-aware review, and practical security controls to public inquiries and project work. Retention periods depend on legal, tax, accounting, contractual, audit, support, security, backup, and dispute-resolution needs.

Client projects may require additional controls, including named systems, access lists, approval gates, deletion steps, export formats, backup rules, audit evidence, and handoff notes.

8. Project-Specific Controls

Project documents may define which providers, models, environments, repositories, datasets, credentials, logs, and automations are approved. They may also define approval thresholds, rollback paths, incident contacts, subprocessors, export rights, and retention windows.

If a requested workflow involves sensitive data, regulated records, payments, medical information, legal decisions, employment decisions, child safety, financial advice, security automation, or public-impacting automation, Hypler may require narrower scope, additional review, or written controls before work starts.

9. Machine-Readable Discovery

Hypler publishes robots.txt, llms.txt, llms-full.txt, per-page Markdown, content-index.json, ai-index.json, ai.txt and ai-use-policy.json. These provide public content and access guidance without JavaScript or authentication. The AI text and JSON manifests are Hypler discovery formats, not execution APIs or universal standards.

  • Agents should prefer canonical public pages over scraped copies, snippets, screenshots, or stale caches.
  • Agents should preserve links, dates, caveats, and source context when summarizing Hypler public content.
  • Agents should not treat public marketing, glossary, demo, or policy text as project-specific legal, security, compliance, procurement, or technical certification advice.

10. Contact

Questions about technical access, AI use, cookies, automated agents, crawler behavior, security reports, or project-specific controls can be sent to contact@hypler.com.