Mibba vs Perplexity

Mibba

AI coworker for French notarial offices, automating workflows while teams stay in control.

Mibba is an AI coworker built specifically for French notarial offices. It helps notaries, clerks and support teams reduce repetitive administrative work without replacing their existing practice-management or CRM systems. Mibba connects the information already spread across matters, emails and documents, then prepares useful work for the team: summarising a matter, identifying missing information, tracking deadlines and pending actions, preparing client follow-ups, organising document-related tasks and surfacing clients who need attention. Every proposed action remains subject to human review and validation. The product is designed for the day-to-day reality of notarial practices, particularly teams of 10 to 30 people handling many active matters in parallel. Instead of acting as a generic chatbot, Mibba maintains the context of each matter and shows the sources behind the information it uses. This helps collaborators resume a file faster, coordinate consistently and spend more time on legal analysis, client advice and relationship-building. Mibba is delivered as a web-based paid subscription with pricing tailored to the roles equipped and the scope selected by each office. Customer data is hosted in France, isolated between customers and never used to train AI models. The platform is built to complement the software already used by the office, so teams can introduce AI-supported workflows without disrupting established processes.

Perplexity

AI-powered answer engine that cites its sources

Perplexity is an AI-powered answer engine that responds to questions in prose with inline citations to the sources it used, positioning itself as a replacement for the search-then-read-ten-tabs loop rather than as a chatbot. The design decision that defines it is citation. A general-purpose model answers from its training data and can be confidently wrong with no way for a reader to check. Perplexity runs a search, reads the results, and composes an answer with numbered references to the pages it drew from, so the claim and its source sit next to each other. That does not eliminate error, but it changes the failure mode from undetectable to checkable - which is the difference between a tool you can use for research and one you cannot. Around that sit follow-up questions that keep the thread's context, Spaces for organising related research, and a Deep Research mode that runs a longer multi-step investigation and returns a structured report. The product is available on the web, on mobile, and as a browser extension. Pricing is freemium: a free tier with a capped number of advanced queries per day, and a Pro subscription that raises limits and grants a choice of underlying frontier models. For founders, there is a second reason this listing matters beyond using the tool. Perplexity is one of the surfaces that now sends - or fails to send - traffic to your site. Being cited in AI answers is becoming its own discipline, and the pages that get cited are the ones that answer a question directly, in a self-contained passage, with clear structure and something specific to say. The comparisons: ChatGPT with search is broader and more conversational but less consistently sourced. Google's AI Overviews reach far more people and cite less generously. Claude is stronger for long-document reasoning and writing. Traditional search still wins when you want to choose your own sources rather than have one chosen for you. Choose Perplexity when you want an answer you can verify, and when the alternative is opening ten tabs to assemble it yourself.