Count

Are you checking Claude's claims? Auditing ChatGPT for hallucinations? Making sure AI's analysis is *actually* sound before sharing? Data, strategy, finance, and executives agree: sharing quality AI-assisted work is hard, and validating against hallucinations is even harder. With Count, turn any AI output into an auditable, shareable output for free. Here’s how: 1️⃣ Start with an AI answer: From Claude, ChatGPT, or any AI app, push your threads and thinking to Count to identify claims. 2️⃣ Check claim credibility: On the canvas, every claim is mapped out. Trace sources, check logic, and see where the LLM's hallucinated. 3️⃣ Challenge reasoning together: Invite your team for free and inspect the results in tandem, and in real-time.

Would your analysis survive a fact-check? Before you share that AI-assisted report - have you actually verified it? Traced the claims? Checked the logic holds? Most teams don't, because there's never been an easy way to. Now there is. Count turns any AI output into an auditable canvas, free: 1️⃣ Push your Claude or ChatGPT thread to Count 2️⃣ Every claim, mapped and traceable 3️⃣ Invite your team, catch the hallucinations together

Are you checking Claude's claims? Auditing ChatGPT for hallucinations? Making sure AI's analysis is *actually* sound before sharing? Data, strategy, finance, and executives agree: sharing quality AI-assisted work is hard, and validating against hallucinations is even harder. With Count, turn any AI output into an auditable, shareable output for free. Here’s how: 1️⃣ Start with an AI answer: From Claude, ChatGPT, or any AI app, push your threads and thinking to Count to identify claims. 2️⃣ Check claim credibility: On the canvas, every claim is mapped out. Trace sources, check logic, and see where the LLM's hallucinated. 3️⃣ Challenge reasoning together: Invite your team for free and inspect the results in tandem, and in real-time.

Are you actually checking Claude's claims? Auditing ChatGPT for made-up numbers? Confirming the analysis holds up before it goes in the deck? Every data, strategy, and finance team says the same thing: validating AI output is the hard part everyone skips. Count turns any AI output into something auditable and shareable - for free: 1️⃣ Push your thread from Claude, ChatGPT, or any AI app 2️⃣ Every claim gets mapped - trace the source, check the logic, spot the hallucination 3️⃣ Bring your team in free to stress-test the reasoning together

Are you checking Claude's claims? Auditing ChatGPT for hallucinations? Making sure AI's analysis is *actually* sound before sharing? Data, strategy, finance, and executives agree: sharing quality AI-assisted work is hard, and validating against hallucinations is even harder. With Count, turn any AI output into an auditable, shareable output for free. Here’s how: 1️⃣ Start with an AI answer: From Claude, ChatGPT, or any AI app, push your threads and thinking to Count to identify claims. 2️⃣ Check claim credibility: On the canvas, every claim is mapped out. Trace sources, check logic, and see where the LLM's hallucinated. 3️⃣ Challenge reasoning together: Invite your team for free and inspect the results in tandem, and in real-time.

Are you actually checking Claude's claims? Auditing ChatGPT for made-up numbers? Confirming the analysis holds up before it goes in the deck? Every data, strategy, and finance team says the same thing: validating AI output is the hard part everyone skips. Count turns any AI output into something auditable and shareable - for free: 1️⃣ Push your thread from Claude, ChatGPT, or any AI app 2️⃣ Every claim gets mapped - trace the source, check the logic, spot the hallucination 3️⃣ Bring your team in free to stress-test the reasoning together