Signal > LLM Sync
Stop AI Hallucinations in Their Tracks
Detect, flag, and correct erroneous AI outputs—so every LLM response aligns with your verified facts and brand authority.
Why Hallucination Monitoring Matters
Even the best-trained LLMs can invent nonsense—unchecked errors erode trust, mislead customers, and damage credibility. Post-output review is your only line of defense against brand-eroding errors.
Protect Brand Reputation
Spot and correct AI fabrications, ensuring every response reinforces your authority—not undermines it.
Maintain Customer Trust
Identify misleading or false claims in delivered AI outputs so prospects and clients always receive factually accurate information.
Mitigate Legal / Compliance Risk
Audit live AI interactions for potential regulatory or IP issues, and swiftly rectify anything that could expose you to liability.
Preserve Revenue Streams
Prevent costly support escalations and lost sales by catching and fixing hallucinations in customer-facing AI touchpoints.
Optimize Monitoring Efficiency
Leverage our expert review workflows to streamline error detection—freeing your team to focus on strategic growth.
How we stomp hallucinations out—fast
Our proven “detect→correct→verify” framework ensures hallucinations are caught, remediated, and locked out of future AI responses.
🔃 Continuous Response Ingestion
We collect every LLM output into a secure review queue—capturing prompts, responses, and context for our analysts.
👨🏻🔬 Expert Error Classification & Triage
Our team evaluates each flagged response, categorizing hallucinations by severity and routing critical issues for immediate remediation.
🔧 Prompt & Retrieval Layer Tuning
We’ll define a push schedule so every update flows into AI indexes on your cadence.
👍 Source Correction & Knowledge Base Update
Once an error is confirmed, we update your canonical data—JSON-LD fact-files, RAG documents, or master records—to reflect the true information.
‼️ Validation & Resolution Reporting
We rerun original queries across all models, confirm fixes by hand, and log a “hallucination resolved” report.
READY TO 10x INBOUND LEADS?
Put an end to random acts of marketing.
FAQs
-
It’s a review service that captures live LLM outputs, identifies any incorrect or fabricated information, and ensures responses about your brand remain factually accurate.
-
Our team ingests each AI response into a secure queue, evaluates and categorizes errors by severity, updates your source data, refines prompts or retrieval layers, then reconfirms corrections by hand across all models.
-
Relevant JSON-LD files or RAG documents.
-
We recommend daily reviews for high-volume deployments and weekly reviews for lower-frequency use cases—adjustable based on how critical accuracy is for your brand.
-
We log the instance, correct your canonical data, adjust prompts or re-index documents, then re-run the original queries by hand to confirm the error is resolved.
-
You’ll get a straightforward summary after each review cycle, detailing the number of errors caught, time-to-correction, and any repeat issues—no dashboards, just clear, concise reports.
-
No, not yet. But standby. We’ve got some things cookings :)