Ema Elisi

Hey Product Hunt! 👋 Ever sat down to plan something—and then stared at a blank screen for 20 minutes? Yeah, us too. That’s why we built Elisi—a planner that feels like it gets you. Not just another “AI tool.” No robotic commands. Just natural, fluid planning. What makes Elisi different? You speak, it listens. Type something like “Prep for team meeting on Thursday, send recap Friday” and Elisi...

@novakben How does the app avoid 'over-reminding' or under-delivering? Can users tweak the cadence or context of nudges, or does the randomness intentionally mimic how wisdom surfaces organically in life?

@zimbra How does the AI ensure lead relevance without risking spam triggers? Does it adapt criteria per campaign, and how do the pre-warmed inboxes stay credible when sending varied content across industries?

@rayevkaniyet How does the platform ensure AI-generated features (like a chatbot or booking screen) inherit the host app’s styling and interaction patterns? Does Boxo auto-adapt components to your theme, or does it require manual oversight to avoid a ‘Frankenstein’ user experience?

@marcin_kurylak@adi_kurian Congrats on launching! How does the AI discern context when the same term (e.g., ‘dispute process’) has different implications per vertical? Does it infer meaning solely from your documentation’s structure, or are there safeguards to flag ambiguities for human review?

@divyanshu2609 @sharmag88Your focus on industry-specific emergencies is compelling! If a panicked customer calls about a ‘weird smell’ near their furnace but doesn’t explicitly say ‘gas leak,’ how does the AI gauge urgency? Can it recognize indirect red flags (like tone or slang) and escalate appropriately, or does it rely on businesses to manually define what phrases trigger emergency protocols?

@0x_s13i For teams where collaboration complexity varies (e.g., a simple solo fix vs. a cross-team refactor), how does the model account for factors like review cycles or architectural discussions that aren’t directly reflected in code output?

@jason_ginsberg For someone managing both client projects and internal team docs in Notion, how does the AI decide which emails to prioritize or link to specific workflows? If an urgent client email arrives, does it surface related project notes automatically, or does it require manual tagging to bridge the gap between inbox and workspace?

@aditi_kothari For teams working across evolving codebases, how does the platform handle drift between an agent’s initial training and later code changes? If a critical dependency gets refactored, does the agent self-correct using semantic search, or does it require manual context updates to stay reliable?

@finn_brown Aqua’s speed across apps is impressive! For someone jumping between a code editor and a casual chat in Slack, how does the tool handle context shifts—like technical jargon vs. colloquial phrases—without tripping over formatting or needing manual adjustments?

@oleg_sobolev Extrovert’s focus on authentic engagement is refreshing! For a team with diverse writing styles, how does the AI adapt when crafting comments—does it learn from each member’s past interactions to mirror their voice, or do you set a unified 'brand tone' upfront?

@danigleba For someone easily pulled into endless videos, how does the tool prevent distractions like ads or suggested content? Does it strip the experience down to just audio, or is there another approach to keep focus intact?

@jariusos Really interesting product! How does the platform verify the accuracy of a fact before it’s accepted? Is there a community-driven moderation layer, automated checks, or expert validation? And if a PK is later challenged or proven wrong, how does LearnPool handle updates or corrections?

@sylviangth MindPal’s multi-agent workflows sound fascinating for automating intricate processes! For someone setting up a client onboarding sequence, I’m curious: how do the agents handle dependencies or conflicting priorities mid-workflow? For example, if one agent drafts a proposal while another pulls outdated client data, does the system flag inconsistencies automatically, or does it rely...

@steve_liu11 @nz_altar For someone who uses scattered tools for notes, bookmarks, and files, I’m wondering: how does ALTAR maintain the connections between these different formats (like a research PDF vs. a casual note) to ensure the AI pulls relevant context? Does it require upfront structuring, or does it infer relationships on its own over time?

@skabhi How does Sherlock distinguish between benign behaviors (e.g., a candidate glancing at notes) and malicious AI cheating—especially as tools like AR glasses or background apps blur the line?​​ For instance, if a candidate uses a secondary device off-camera to query ChatGPT, how does the system infer this without invasive screen monitoring? Are detection models trained on real-world...

@david_connors The platform’s ability to unify fragmented relationship data (investors, alumni, work history) into scored, actionable insights could finally solve the "who do we know at X?" problem plaguing sales teams. David’s track record (Automately.io → Sequoia) adds weight, and the multi-access strategy—API, SaaS, Clay/LinkedIn integrations—shows flexibility for both builders and...

@ansub Agno’s focus on speed, multimodal flexibility, and open-source ethos makes it a tantalizing foundation for developers pushing agentic systems beyond today’s latency-heavy norms. The claims around memory efficiency and multi-agent orchestration could redefine how teams scale AI workflows. But ​​how does Agno handle resource contention in complex, real-world deployments​​—say, when 100+...