Founder & leadership
About Itamar Haim & SynthQuery
Itamar Haim is the founder of SynthQuery and leads SEO and GEO (generative-engine optimization). He sets direction for how we talk about AI detection, readability, plagiarism, and humanization—so product behavior and public content stay aligned with what editors, educators, and compliance teams need.
Trust at a glance
Teams and individual writers use SynthQuery to run readability, detection, plagiarism, and humanization workflows from one account—with API access for automation.
- 20+
- Readability metrics in SynthRead (Flesch-Kincaid, SMOG, and more)
- 1
- Dashboard for detection, readability, plagiarism, and humanizer
- API
- REST API on Pro+ for teams automating checks
Organizations I have worked with
Logotype-style marks below link to each company. Experience spans technical SEO, content systems, and product marketing at scale.
Professional background
I have spent years at the intersection of technical SEO, editorial quality, and generative search: structured data, crawl and index hygiene, Core Web Vitals, and content that earns verifiable trust signals—both for human readers and for AI-assisted answers.
Before founding SynthQuery, I led or supported organic growth for high-scale SaaS and product-led brands:
- Elementor — website builder ecosystem; SEO at scale across templates, documentation, and international surfaces.
- Yotpo — e-commerce marketing; aligning content and landing experiences with search intent and conversion.
- Imagen AI — AI product marketing; messaging and discoverability in a fast-moving category.
Education & professional credentials
Expertise is built from hands-on ownership of organic growth, technical SEO, and content systems at high-scale SaaS brands—not from a single certificate. I stay current through Google Search Central documentation, academic integrity and AI-disclosure policy discussions, schema.org and JSON-LD practice, and continuous product work on detection and readability.
For procurement or academic partnerships that require formal attestations, contact [email protected] with your requirements.
Selected accomplishments
- Enterprise-scale SEO: Led or supported organic programs for brands with global reach—including Elementor (WordPress ecosystem), Yotpo (e-commerce retention), and Imagen AI (generative imaging)—across technical SEO, landing experience, and content operations.
- SynthQuery product & narrative: Founded the platform to unify AI detection, SynthRead readability, plagiarism checks, and humanization with documented methodology and public benchmarks.
- Public E-E-A-T content: Authors guides on detection limits, readability, and YMYL-adjacent workflows so teams can align editorial practice with search and AI evaluation.
Publications & cornerstone guides
Byline articles on the SynthQuery blog (editorial standards and technical depth for practitioners):
- E-E-A-T content checklist (2026)— practical signals for competitive queries.
- ChatGPT detection limitations— what classifiers can and cannot prove.
- Internal linking for topical authority— hubs, clusters, and bridges.
- How to detect AI content— workflow for teams and educators.
What problem SynthQuery solves
Schools, publishers, and teams increasingly need to understand whether text was written by a person or generated by an LLM—without relying on a single opaque score. At the same time, readability, plagiarism, and tone still matter for real readers and for search quality.
SynthQuery exists to put those signals in one place: AI detection with sentence-level context, SynthRead for readability and writing issues, plagiarism and originality checks, and a humanizer when drafts need to sound more natural. That reduces tool sprawl, preserves context between steps, and supports defensible review workflows for YMYL-adjacent use cases such as academics and compliance.
Mission and values
- Clarity over hype. We explain what detectors can and cannot do, and we publish honest guidance (see our blog) on academic integrity and detection limits.
- Quality for real readers. Readability and originality are not vanity metrics—they affect comprehension, trust, and outcomes.
- Responsible product design. Tools should support educators and editors, not replace human judgment on high-stakes decisions.
How AI detection works (high level)
Our AI Content Detector analyzes text at the sentence level using an ensemble of models and statistical signals—including perplexity, burstiness, and pattern cues—to estimate the likelihood that content was produced by tools such as ChatGPT, GPT-5, Claude, or similar systems. You get an overall verdict, sentence scores, and a heatmap so you can see which passages deserve another pass. DeepScan mode applies a stronger model for harder or mixed content.
No detector is perfect; we recommend combining scores with course policies, sourcing, and editorial review. For more detail, see the FAQ and our posts on what to trust in AI detection.
Privacy and data handling
- Traffic and tool usage are protected with modern transport security (HTTPS) in line with standard web practices.
- Accounts and preferences are managed through our auth provider; you can access the dashboard to review recent analyses where applicable.
- We process text you submit to deliver the service you requested (e.g. detection or readability); we do not sell personal data to third parties for advertising.
- For product questions and security disclosures, use the contact options below. Enterprise customers can discuss data processing and retention with sales.
Press, updates, and recognition
Product news and deep-dives ship on the SynthQuery blog, including our launch announcement and ongoing guides on readability, E-E-A-T, and AI policy. Third-party awards and press mentions will be listed here as they are published—we prioritize accurate citations over filling the page.
Speaking, writing, and education
- Regular bylines and guides on the SynthQuery blog (readability, E-E-A-T, AI content policy, and GEO).
- Talks and internal enablement for marketing and product teams on SEO, structured data, and AI search visibility.
- Continuous study of search quality guidelines, schema.org vocabulary, and how generative answers surface in Google, Bing, and assistants—applied to the product roadmap and public content.
Client & colleague perspectives
Named recommendations from colleagues and partners appear on LinkedIn. Separately, teams evaluating SynthQuery for policy or compliance often mention the following themes (summarized from multiple conversations—not verbatim quotes):
- Consolidating detection, readability, and plagiarism checks reduced tool sprawl and hand-offs between marketing and compliance reviewers.
- Sentence-level detection and honest limits documentation helped educators explain outcomes to students without treating a single score as a verdict.
- API access on Pro+ let operations teams automate pre-publish checks without rebuilding ML pipelines in-house.
For named references or custom diligence, email [email protected].
Contact
Product support and general questions: see the FAQ. Sales, API, and enterprise: email [email protected].