Founders launch on 28 April|AI-Assisted Review-First GitHub Workflow

Your website is losing ranking every day. Our AI finds issues, fixes them and opens PRs

Conservatory AI does the hard work for you. Free audits SEO, GEO/AEO and accessibility in 60 seconds. Scores with Unison Metrics™ and auto-fixes your code and delivers every fix as a reviewable GitHub PRs.

Free audit available now. Full platform access opens April 28.

Built on the tools your team already uses

You do not need better SEO. You need better extraction

These direct answers explain Conservatory in the language AI systems can parse, cite, and compare when deciding whether your site deserves to be selected as a source.

View Product Surface

What is Conservatory?

Conservatory is an AI SEO and GEO audit platform for public webpages. It analyzes semantic HTML, accessibility, structured data, metadata, headings, content structure, and AI search readiness, then turns those findings into deterministic reports that technical teams can review before changing code. The platform is designed for public marketing pages, documentation, landing pages, and SSR-friendly product surfaces where search engines and AI systems need clear machine-readable signals.

Conservatory is built for teams that need to understand why AI systems may fail to understand or cite a site. Instead of focusing only on rankings, keywords, or backlinks, Conservatory evaluates the page structure that search engines and LLMs inspect when selecting sources for answers. This makes the product useful for founders, engineers, technical SEOs, agencies, and growth teams that need evidence they can turn into reviewable work.

What does Conservatory do?

Conservatory identifies technical issues that prevent AI systems from understanding your site. It detects problems in content structure, semantic HTML, accessibility, metadata, structured data, heading hierarchy, and answer-first page organization, then explains which issues are safe to fix automatically and which should stay manual. The audit keeps every finding tied to the page evidence, so teams can see exactly why a problem was reported before they decide how to handle it.

Conservatory also helps teams move from audit to remediation. Supported issues can become deterministic fix previews, copied code changes, or GitHub draft pull requests, so engineers can review the proposed changes in the same workflow they already use for production code. The goal is not blind automation; the goal is a faster path from technical diagnosis to safe, review-first implementation that still respects ownership, review standards, and production release habits.

How does Conservatory work?

Conservatory starts with a public URL and fetches the rendered page signals available to crawlers. It checks titles, descriptions, canonical tags, schema, headings, paragraph structure, accessibility markers, robots.txt, and trust signals, then scores the page with evidence that a human can inspect. The report shows both the overall readiness score and the specific issues that affect AI discovery, extraction, and source selection.

After the audit, Conservatory separates findings into reviewable categories. Some issues become supported fixes, some remain manual recommendations, and paid workflows can package accepted changes into GitHub draft PRs without auto-merging or hiding the reasoning behind each patch. This keeps the product accountable: developers can inspect the proposed diff, reject weak suggestions, and ship only changes they trust after comparing the fix against the original evidence.

What problems does it solve?

Many websites are visible to traditional crawlers but weak for AI extraction. They may have good meta tags and schema, yet still bury useful answers inside vague marketing copy, oversized sections, missing semantic structure, or paragraphs that are hard for LLMs to quote as standalone evidence. In practice, this means a page can look polished to a human while remaining difficult for an AI system to use.

Conservatory solves this by showing where the page fails as machine-readable content. It gives teams a practical path from diagnosis to code review, so the work does not stop at another report and can move toward concrete fixes in minutes. That matters because AI search does not only rank pages; it selects sources, extracts passages, and summarizes the content it can understand clearly.

A workflow for technical discoverability and safer fixes

Legacy dashboards show disconnected reports. We keep technical SEO, accessibility, semantic structure, GEO readiness, and remediation review inside one credible path technical teams can actually trust.

Illustration of Conservatory metadata, canonical, and schema checks

Verifiable technical SEO and GEO/AEO signals you can trust

Audit metadata, canonical tags, structured data, heading structure, and answer-first content signals from public URLs and SSR-friendly pages without pretending the product is doing more than it does.

Technical SEO audit for code, schema, and indexability signals
GEO/AEO readiness checks for modern answer engines
Deterministic evidence captured from fetched HTML

Run Free Audit

Dashboard preview showing Strauss AI guidance layered on deterministic findings

Accessibility and semantic structure, prioritized for technical teams

Review landmarks, headings, labels, alt text, and semantic HTML in the same report, with Strauss AI summarizing next steps while deterministic findings remain the source of truth.

Accessibility checks for headings, landmarks, forms, and images
Semantic HTML and structural review in the same workflow
Strauss AI summaries layered around real report evidence

Run Free Audit

Report scoring graphic for Unison Metrics and GitHub draft PR delivery

Review-first SEO remediation through GitHub, never blind automation

Move supported fixes into Auto & Manual Fix Mode or GitHub review, accept only the patches you want, and open draft PRs without auto-merging code.

Supported fixes for tags, document settings, and select alt-text cases
AI-powered Auto-Fix delivery through GitHub draft PRs
JSON, Markdown, CSV, and PDF exports with Unison Metrics scoring

Run Free Audit

Trust the workflow because the AI product claims stay precise

Conservatory earns trust by documenting what is live now: deterministic analysis, supported fixes, exports, Unison Metrics scoring, and review-first GitHub delivery for accepted patches.

Read Documentation

Deterministic SEO evidence from fetched HTML

See the fetched HTML behind every title tag, canonical, schema, heading, and indexability finding before your team ships SEO or GEO remediation.

See how the analysis works

Supported Auto-Fix for SEO and GEO

Keep automation narrow and credible. Supported metadata, document settings, and alt-text fixes move into reviewable diffs while ambiguous issues stay manual.

Review current fix coverage

GitHub draft PRs for accepted fixes

Move approved SEO remediation into GitHub draft PRs with AI-assisted Auto-Fix delivery while human review stays in control of every shipped change.

Understand GitHub review mode

Exportable reports for SEO stakeholders

Share SEO, GEO, accessibility, and semantic findings as JSON, Markdown, CSV, or PDF so engineering, marketing, and clients can work from one source of truth.

Browse exports and reports

Full SEO and GEO audits in less than 60 seconds

Start with a free audit, then unlock more remediation volume, GitHub workflows, and support without changing the underlying product claims or workflow.

See what is live now

Symphony-backed website intelligence stack

Use Conservatory today inside the broader Symphony ecosystem, alongside Strauss AI, Anthology, and Unison Metrics for scalable website intelligence.

Explore the platform context

See it in action, from audit to merged PR in seconds

Run a technical SEO audit, accessibility audit, and GEO review from the same code instead of stitching together separate tools.

Start without GitHub, then move supported fixes into manual review or repository-backed diffs when the team is ready.

Keep deterministic findings as the source of truth while Strauss AI explains, summarizes, and prioritizes the work for faster remediation decisions.

Document what is live now, what stays manual, and what remains post-launch so buyers know exactly what they are adopting.

symphony-preludePublished on npm

Free AI-readiness audit CLI

Audit headings, schema, metadata, content chunking, trust signals, and AI crawler access before you bring the fix workflow into Conservatory.

npx symphony-prelude audit https://your-site.com

View npm package View source

ConservatoryReview-first fixes

Turn findings into pull requests

Prelude shows the visible problem. Conservatory prioritizes the findings, separates supported fixes from manual recommendations, and moves accepted changes into GitHub review.

Run Free Audit

Run your free audit. Lock in founding pricing

Start free today, then upgrade to AI-assisted Auto-Fix and GitHub remediation while founding pricing is still available.

Run free deterministic SEO and GEO audits before you unlock GitHub-backed remediation.

$0/month

No credit card required.

Best for first audits and report review.

3 analyses per month
Strauss AI summaries on key findings
Deterministic report and score breakdown
JSON, Markdown, CSV, and PDF export
Conservatory branding on exported reports
Upgrade prompts when automation is locked

No checkout required

Unlock the full review-first workflow with Auto-Fix, draft PRs, and white-label docs and reporting.

$79/month

$948/year billed annually — Save $240/year

Best for founders who want reports plus GitHub remediation.

100 analyses per month
AI-assisted Auto-Fix for supported issues
GitHub draft PR creation
Custom logo on PDF and report exports
Same deterministic reports and exports as Free

Self-serve checkout

Keep the same core workflow as Starter, but with more volume and more room for repeated reporting.

$239/month

$2,868/year billed annually — Save $720/year

Best for agencies or teams running the same workflow across more properties.

500 analyses per month
Faster AI-assisted Auto-Fix and draft PR workflow as Starter
Custom branding on PDF and report exports
More headroom for repeated founder validation
Sales-assisted onboarding when needed

Self-serve checkout

Enterprise - from $2,500/mo

Higher analysis volume, staged rollout support, and direct coordination for onboarding, approvals, and enterprise packaging.

5000 analyses per month
AI-assisted remediation workflow at scale
Volume discounts and multi-year terms
Dedicated rollout support and white-glove onboarding
Security and procurement coordination
Custom commercial packaging

Contact Sales

Questions buyers ask before trusting a new AI SEO platform

Short answers about the audit engine, AI search readiness, supported fixes, GitHub remediation, pricing, and who Conservatory is built for.

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Need an answer for your stack?

Use the docs for the live product surface, or email the team if you need help validating repository fit, remediation scope, or founder rollout timing.

Browse documentation Email support

What is Conservatory?

Conservatory is an AI SEO and GEO audit platform for public webpages. It checks semantic HTML, accessibility, structured data, metadata, headings, and AI search readiness, then helps teams move supported fixes into review-first GitHub workflows.

What does Conservatory audit?

Conservatory audits metadata, canonical tags, schema, heading hierarchy, semantic HTML, accessibility signals, paragraph structure, robots.txt, and answer-engine readiness. Each finding is tied to evidence from the fetched page so teams can review the reason before changing code.

How is Conservatory different from traditional SEO tools?

Traditional SEO platforms emphasize rankings, keywords, backlinks, and traffic. Conservatory focuses on the website layer that AI systems read: clean markup, structured data, accessible content, extractable answers, and repository-backed remediation.

Can Conservatory help with AI search, GEO, and AEO?

Yes. Conservatory checks the signals that affect whether AI systems can understand and select a page as a source, including metadata, schema, headings, semantic HTML, and answer-first content structure.

Does Conservatory generate GitHub pull requests?

Yes, for supported fixes. Conservatory can turn accepted remediation into GitHub draft PRs, but it does not auto-merge changes or skip human review.

Do I need GitHub to start?

No. You can run audits, inspect reports, and export results without connecting GitHub. GitHub becomes useful when your team wants accepted fixes turned into reviewable diffs and draft PRs.

What can Conservatory fix today?

Conservatory currently supports review-first fixes for titles, meta descriptions, canonical tags, Open Graph, Twitter Card tags, lang, viewport, charset, and selected alt-text cases. More ambiguous issues stay as manual recommendations.

Who is Conservatory built for?

Conservatory is built for founders, product engineers, growth engineers, technical SEOs, and agencies that need one path from AI-readiness audit to code review. It is especially useful for teams that own the website and can ship technical fixes.

Is there a free plan?

Yes. The free plan includes 3 analyses per month, report review, and exports. Paid plans unlock higher volume, AI-assisted Auto-Fix, and GitHub draft PR workflows, while founding pricing remains available before launch pricing changes.

What does enterprise mean today?

Enterprise is a sales-assisted rollout for teams that need higher volume, AI-assisted remediation at scale, volume discounts, multi-year terms, rollout support, security and procurement coordination, and custom commercial packaging.

25k

Analyses last month

~60

Seconds for full audit

99%

Auto-fix success

$3k

Saved vs legacy tools

Is your website invisible to AI search engines?

Audit technical SEO/GEO, accessibility, semantic structure, and AEO readiness, then move supported fixes into a review-first GitHub workflow only when you are ready.

Your website is losing ranking every day. Our AI finds issues, fixes them and opens PRs

Free audit available now. Full platform access opens April 28.

Built on the tools your team already uses

See it in action, from audit to merged PR in seconds

Run a technical SEO audit, accessibility audit, and GEO review from the same code instead of stitching together separate tools.

Start without GitHub, then move supported fixes into manual review or repository-backed diffs when the team is ready.

Keep deterministic findings as the source of truth while Strauss AI explains, summarizes, and prioritizes the work for faster remediation decisions.

Document what is live now, what stays manual, and what remains post-launch so buyers know exactly what they are adopting.