Adjuro vs AEO Table

Adjuro and AEO Table are both business tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Adjuro

The vendor describes an API service that issues cryptographically signed consent receipts at the moment an outbound AI voice call is authorized, creating a tamper-evident record tied to that specific interaction. Legal teams get exportable evidence packets formatted for discovery, without having to reverse-engineer call logs or depose platform engineers. The records are designed for third-party verification without granting platform access — which matters when opposing counsel demands proof and you cannot hand over your production environment. The ceiling appears when your compliance posture requires self-hosted data residency; the vendor states no self-hosted deployment option exists. Teams with data sovereignty mandates will need to resolve that before signing a contract.

AEO Table

AEO Table addresses that gap by running structured queries across ChatGPT, Google AI Overview, and Perplexity, then freezing each run as an immutable snapshot so you can compare what AI channels said last month against what they say now. The core loop is four steps: define your brand, scope a task with target questions and competitors, trigger a run, and pull a report with citations intact. It works well for teams that need repeatable evidence — share-of-answer metrics, competitor appearances, and the source domains driving citations. The ceiling arrives fast for teams that need to act on that evidence programmatically: there is no API, no webhook, and no way to pipe results into your existing data stack without manual export.

Attribute	Adjuro	AEO Table
Pricing	Paid	Paid
Price	—	$20/mo
Free trial	No	No
Open source	No	No
Has API	Yes	No
Self-hosted option	No	No
Platforms	Cloud API (SaaS); vendor-agnostic; integrates with any outbound voice platform	Web-based SaaS
Pros	Signed receipts are issued at call time via API, so consent is documented at the moment it exists — not reconstructed from logs after a lawsuit is filed, which is the record opposing counsel attacks first. Evidence packets are pre-formatted for discovery, which means legal teams avoid the deposition risk of having a platform engineer explain how the export was assembled. Third-party verification works without granting platform access, so opposing counsel can confirm record authenticity without your production environment becoming part of discovery. Usage-based pricing per call and evidence export, so compliance costs scale with actual campaign volume rather than requiring a flat infrastructure commitment before you know litigation exposure. API-first design, so the receipt-issuance step integrates directly into the call authorization path of an existing AI voice platform without requiring a separate compliance workflow.	Immutable Run snapshots freeze the exact question set, providers, and competitor scope alongside the answer evidence, so month-over-month comparisons don't silently shift when AI models update — which means you can defend 'visibility dropped in March' with a timestamped record rather than a hunch. Citation-level evidence shows which source domains AI channels are pulling from when they mention or skip your brand, so content and SEO teams can prioritize which third-party placements actually drive AI visibility instead of optimizing in the dark. Cross-provider coverage across ChatGPT, Google AI Overview, and Perplexity in a single task run, so you avoid maintaining three separate manual query logs to get a consolidated picture of where your brand stands in AI-generated answers. Public share links and PDF export let account managers deliver polished visibility reports to clients or executives without requiring stakeholders to log in, which removes the friction that normally turns good data into a slide that never gets acted on. Multi-brand and multi-task structure means an agency managing ten clients can scope each monitoring job independently — separate question sets, competitor lists, and markets — without runs from one client contaminating the evidence for another.
Cons	No self-hosted deployment option exists — consent records are stored in the vendor's infrastructure. Teams subject to data residency mandates or requiring on-premises control of legally sensitive records hit this wall at contract review, not after integration, and the next step is building internal cryptographic signing infrastructure. The scraped page content does not match the described tool — the validator flagged this as an API service for consent receipts, but the source page returned content for an unrelated mobile app. Teams evaluating this tool cannot independently verify API documentation, integration specs, or uptime commitments from the public-facing page, which means due diligence requires direct vendor engagement before any architecture decisions. A team running campaigns across jurisdictions with consent requirements that exceed TCPA — GDPR, for example, or state-level equivalents — will find that the tool's described scope is TCPA-specific. Expanding compliance coverage to those regimes requires either additional tooling or confirming with the vendor that the receipt schema maps to those standards.	There is no API and no webhook, so every run result lives inside the platform until someone manually exports it. Teams that need AI visibility data joined to a BI dashboard, CRM, or performance report have no automated path — they copy, paste, or download PDFs. When that friction compounds across weekly runs for multiple clients, the manual overhead becomes the bottleneck. The credit-based model caps how many queries you can run on the free tier, and the docs describe the free allocation as a one-time launch grant rather than a recurring allowance. Teams that want daily or high-frequency monitoring hit the credit ceiling and must move to a paid tier — at which point they are evaluating cost per run against building their own query layer on top of provider APIs. Monitoring is limited to ChatGPT, Google AI Overview, and Perplexity. Teams that need visibility into Bing Copilot, Claude, Gemini, or regional AI answer surfaces have no coverage here. When a client's target market skews toward a provider not on the list, the platform's evidence set is structurally incomplete — and teams in that position move toward custom monitoring solutions that can target arbitrary endpoints.

Bottom line

Only Adjuro exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Adjuro and AEO Table?

Adjuro is Paid, while AEO Table is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Adjuro better than AEO Table?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.