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Weekly Top Upvotes
Total Products
10
Avg Upvotes
404
Avg Comments
74
Weeks of Data
1
Aug 2026 · W5Top 10
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1X
x1
X1 is an AI app builder that takes you from an idea to an iPhone app you can publish on the App Store. Instead of trying to generate the entire app from one prompt, X1 guides you step by step. It asks focused questions, designs each screen for you to review and edit, then builds the app in stages. Preview and test it on your iPhone as you go. When it’s ready, X1 prepares your App Store listing, screenshots, and submission. No coding required.
50377
1
X
x1
X1 is an AI app builder that takes you from an idea to an iPhone app you can publish on the App Store. Instead of trying to generate the entire app from one prompt, X1 guides you step by step. It asks focused questions, designs each screen for you to review and edit, then builds the app in stages. Preview and test it on your iPhone as you go. When it’s ready, X1 prepares your App Store listing, screenshots, and submission. No coding required.
503
upvotes
77
comments
What users love
Guided, step-by-step workflow uses focused questions, planning, and screen-by-screen review instead of a one-shot prompt.
Can help non-coders build real, working iPhone apps; users praised its ability to reach a finished, polished result.
Iterative milestone-based building and testing on an iPhone is seen as more controlled and coherent than typical AI builders.
Simple onboarding and a strong UI/building experience received positive feedback.
One user praised the tool for keeping ideas realistic rather than making unsupported promises.
Areas for improvement
One user reported that after leaving the builder, they could not find or reopen the project from the home page, making progress appear lost.
Reviewers repeatedly sought clarification on important capabilities and workflow coverage, including API integrations, native iOS features, authentication, payments, export, and App Store signing/compliance.
What users love
Guided, step-by-step workflow uses focused questions, planning, and screen-by-screen review instead of a one-shot prompt.
Can help non-coders build real, working iPhone apps; users praised its ability to reach a finished, polished result.
Iterative milestone-based building and testing on an iPhone is seen as more controlled and coherent than typical AI builders.
Simple onboarding and a strong UI/building experience received positive feedback.
One user praised the tool for keeping ideas realistic rather than making unsupported promises.
Areas for improvement
One user reported that after leaving the builder, they could not find or reopen the project from the home page, making progress appear lost.
Reviewers repeatedly sought clarification on important capabilities and workflow coverage, including API integrations, native iOS features, authentication, payments, export, and App Store signing/compliance.
2
PaymentKit
PaymentKit is a multi-processor billing platform for SaaS and e-commerce. It routes payments across processors, vaults tokens independently, and keeps subscriptions billing even if a MID gets shut down. No code to launch, full API when you need it.
455106
2
PaymentKit
PaymentKit is a multi-processor billing platform for SaaS and e-commerce. It routes payments across processors, vaults tokens independently, and keeps subscriptions billing even if a MID gets shut down. No code to launch, full API when you need it.
455
upvotes
106
comments
What users love
Multi-processor failover is valued for keeping recurring subscriptions running during processor outages or MID shutdowns without requiring customers to update cards or revisit checkout.
Independent token vaulting is seen as a way to reduce processor lock-in and make future processor changes less painful.
A user who has used the product for several months praised the simple, seamless integration and successfully created routing rules before moving most or all payments through PaymentKit.
Users value configurable payment routing, including the potential to route by region, payment type, reliability, or fees and to test a processor with a small traffic share.
Cross-processor visibility into approval rates, fees, and processor/MID risk is viewed as potentially valuable for identifying issues and managing dispute-ratio exposure.
Areas for improvement
Reviewers want clearer documentation of independent token ownership and portability, especially for network tokens and Apple Pay/Google Pay tokens.
Refund, dispute, chargeback, and consolidated reporting workflows across multiple processors are unclear.
Users request evidence of performance outcomes, particularly soft-decline recovery results from the company's own portfolio.
The effort and timing to migrate active subscriptions, add or remove processors, and export tokens/billing data are not clearly established.
Pricing for smaller teams and the planned breadth of processor integrations remain unclear.
What users love
Multi-processor failover is valued for keeping recurring subscriptions running during processor outages or MID shutdowns without requiring customers to update cards or revisit checkout.
Independent token vaulting is seen as a way to reduce processor lock-in and make future processor changes less painful.
A user who has used the product for several months praised the simple, seamless integration and successfully created routing rules before moving most or all payments through PaymentKit.
Users value configurable payment routing, including the potential to route by region, payment type, reliability, or fees and to test a processor with a small traffic share.
Cross-processor visibility into approval rates, fees, and processor/MID risk is viewed as potentially valuable for identifying issues and managing dispute-ratio exposure.
Areas for improvement
Reviewers want clearer documentation of independent token ownership and portability, especially for network tokens and Apple Pay/Google Pay tokens.
Refund, dispute, chargeback, and consolidated reporting workflows across multiple processors are unclear.
Users request evidence of performance outcomes, particularly soft-decline recovery results from the company's own portfolio.
The effort and timing to migrate active subscriptions, add or remove processors, and export tokens/billing data are not clearly established.
Pricing for smaller teams and the planned breadth of processor integrations remain unclear.
3
akta.pro
Private company data with 4x the depth and 2x the coverage of PitchBook, plus 100+ event signals and news across companies, industries, and topics. Source and diligence deals or make outreach lists and trigger outbound. Built for financial services and GTM teams, pay-as-you-go.
42883
3
akta.pro
Private company data with 4x the depth and 2x the coverage of PitchBook, plus 100+ event signals and news across companies, industries, and topics. Source and diligence deals or make outreach lists and trigger outbound. Built for financial services and GTM teams, pay-as-you-go.
428
upvotes
83
comments
What users love
API-first access to private-company data is viewed as more developer- and AI-agent-friendly than dashboard-only research tools.
Combining structured company profiles with event signals such as funding and hiring gives users richer, actionable context.
Consumption-based pricing is praised as a better fit for bursty enrichment and agent workflows than per-seat subscriptions.
Broad company coverage and a large set of structured fields are seen as valuable for research and outreach use cases.
Upstream entity resolution is appreciated for keeping company data organized and making the API cleaner for developers.
Areas for improvement
Several reviewers question how quickly company profiles and event signals are updated, especially for fast-changing private companies.
Data freshness and reliability for companies with little public information remain a concern.
Users want clearer controls to reduce noise and identify only the signals relevant to their workflows.
Reviewers request customizable signals, triggers, and notifications/webhooks for company events.
Some users want source transparency for synthesized fields and scoring, including the underlying evidence and scoring inputs.
What users love
API-first access to private-company data is viewed as more developer- and AI-agent-friendly than dashboard-only research tools.
Combining structured company profiles with event signals such as funding and hiring gives users richer, actionable context.
Consumption-based pricing is praised as a better fit for bursty enrichment and agent workflows than per-seat subscriptions.
Broad company coverage and a large set of structured fields are seen as valuable for research and outreach use cases.
Upstream entity resolution is appreciated for keeping company data organized and making the API cleaner for developers.
Areas for improvement
Several reviewers question how quickly company profiles and event signals are updated, especially for fast-changing private companies.
Data freshness and reliability for companies with little public information remain a concern.
Users want clearer controls to reduce noise and identify only the signals relevant to their workflows.
Reviewers request customizable signals, triggers, and notifications/webhooks for company events.
Some users want source transparency for synthesized fields and scoring, including the underlying evidence and scoring inputs.
4
Skydive
Build cloud agent coworkers that take on real, multi-step work across the tools you already use. Describe the outcome you want, and Skydive creates a working agent in minutes. No code, no prompt engineering, no workflow wiring required. Skydive agents live in your stack, execute repeatable work, and get sharper over time.
422118
4
Skydive
Build cloud agent coworkers that take on real, multi-step work across the tools you already use. Describe the outcome you want, and Skydive creates a working agent in minutes. No code, no prompt engineering, no workflow wiring required. Skydive agents live in your stack, execute repeatable work, and get sharper over time.
422
upvotes
118
comments
What users love
Agents execute multi-step work across existing tools rather than only answering in chat, reducing cross-tool orchestration effort.
Outcome-based agent creation is easy to use: users can describe the desired work instead of writing prompts, code, or workflow logic.
Specialized agents can build domain expertise from external best-practice sources for tasks such as Stripe disputes, affiliate fraud, and payments.
Agents can be used across web, CLI, and iMessage, supporting work away from a desktop.
Persistent context across platforms and multi-agent handoffs are viewed as promising for larger, ongoing workflows.
Areas for improvement
Permission controls for access to production tools and company data are unclear; multiple reviewers asked how teams control what agents can access or change.
Human-in-the-loop behavior is unclear, including when an agent asks for input versus acting autonomously.
The self-improving mechanism may reinforce near-miss outputs when users do not explicitly provide corrections; reviewers want a way to mark past work as incorrect.
Messaging-channel coverage appears incomplete or unclear, with Telegram support requested.
Some prospective users still need a clearer explanation of the product's concrete use cases and benefits.
What users love
Agents execute multi-step work across existing tools rather than only answering in chat, reducing cross-tool orchestration effort.
Outcome-based agent creation is easy to use: users can describe the desired work instead of writing prompts, code, or workflow logic.
Specialized agents can build domain expertise from external best-practice sources for tasks such as Stripe disputes, affiliate fraud, and payments.
Agents can be used across web, CLI, and iMessage, supporting work away from a desktop.
Persistent context across platforms and multi-agent handoffs are viewed as promising for larger, ongoing workflows.
Areas for improvement
Permission controls for access to production tools and company data are unclear; multiple reviewers asked how teams control what agents can access or change.
Human-in-the-loop behavior is unclear, including when an agent asks for input versus acting autonomously.
The self-improving mechanism may reinforce near-miss outputs when users do not explicitly provide corrections; reviewers want a way to mark past work as incorrect.
Messaging-channel coverage appears incomplete or unclear, with Telegram support requested.
Some prospective users still need a clearer explanation of the product's concrete use cases and benefits.
5
Diet Claude
Hitting Claude's limit mid-work is annoying af. Diet Claude gives a live usage meter shows how much of your session you’ve used, how much time is left, and when your limits reset. It helps optimise token usage by context trimming, tightening prompts, suggesting apt models. And when you do run dry, it carries your conversation and context over to another LLM instead of starting from scratch.
41146
5
Diet Claude
Hitting Claude's limit mid-work is annoying af. Diet Claude gives a live usage meter shows how much of your session you’ve used, how much time is left, and when your limits reset. It helps optimise token usage by context trimming, tightening prompts, suggesting apt models. And when you do run dry, it carries your conversation and context over to another LLM instead of starting from scratch.
411
upvotes
46
comments
What users love
Real-time Claude usage and rate-limit tracking helps users avoid interruption mid-workflow.
Clear visibility into remaining session capacity and reset timing reduces token-limit anxiety.
Memorable Diet Coke-inspired branding, retro pixel widget design, and can-opening sound create a fun experience.
Free Chrome extension is seen as practical for Claude users, especially those on lower-tier plans.
Users value the potential to stretch available Claude usage and manage tokens more efficiently.
Areas for improvement
No native macOS/desktop option was mentioned; users asked to view the meter while working in the desktop version.
Users are uncertain about setup requirements, indicating onboarding or installation instructions may need to be clearer.
A reviewer raised concern that moving to another AI provider can lose conversation context or cause misunderstanding.
A user asked whether it can switch between different Claude Code licenses, suggesting multi-account/license support is not clear or may be missing.
What users love
Real-time Claude usage and rate-limit tracking helps users avoid interruption mid-workflow.
Clear visibility into remaining session capacity and reset timing reduces token-limit anxiety.
Memorable Diet Coke-inspired branding, retro pixel widget design, and can-opening sound create a fun experience.
Free Chrome extension is seen as practical for Claude users, especially those on lower-tier plans.
Users value the potential to stretch available Claude usage and manage tokens more efficiently.
Areas for improvement
No native macOS/desktop option was mentioned; users asked to view the meter while working in the desktop version.
Users are uncertain about setup requirements, indicating onboarding or installation instructions may need to be clearer.
A reviewer raised concern that moving to another AI provider can lose conversation context or cause misunderstanding.
A user asked whether it can switch between different Claude Code licenses, suggesting multi-account/license support is not clear or may be missing.
6
Enter Pro
Building what runs a business takes more than code. Enter Pro is the AI-native platform that turns an idea into a working product. Plan, build, preview, launch, and scale apps, websites, and custom AI agents in one continuous workspace. Models, databases, authentication, hosting, payments, analytics, and localization are built in—so teams can ship software built for real business, not just prototypes.
38568
6
Enter Pro
Building what runs a business takes more than code. Enter Pro is the AI-native platform that turns an idea into a working product. Plan, build, preview, launch, and scale apps, websites, and custom AI agents in one continuous workspace. Models, databases, authentication, hosting, payments, analytics, and localization are built in—so teams can ship software built for real business, not just prototypes.
385
upvotes
68
comments
What users love
Unified workspace for building apps and custom AI agents, praised as making AI part of real workflows rather than a separate chatbot.
Built-in production services—authentication, databases, payments, deployment/hosting, and analytics—reduce the need to configure multiple tools.
Fast, direct workflow for turning an idea into a live product, including live editing and one-click sharing.
Dogfooding the platform for its own CMS and forum increases credibility that it can support real production use.
Built-in localization is valued by teams planning to serve multiple markets.
Areas for improvement
Collaboration capabilities are unclear, particularly simultaneous editing, version history, and branching.
Reviewers want proof that complex applications can scale and remain maintainable beyond an initial prototype.
Recovery and debugging workflows are unclear when AI-generated changes break an existing feature.
The level of developer control over infrastructure, custom configurations, integrations, and connectors is not clearly demonstrated.
Support for existing applications and flexibility in choosing underlying AI models are unclear.
What users love
Unified workspace for building apps and custom AI agents, praised as making AI part of real workflows rather than a separate chatbot.
Built-in production services—authentication, databases, payments, deployment/hosting, and analytics—reduce the need to configure multiple tools.
Fast, direct workflow for turning an idea into a live product, including live editing and one-click sharing.
Dogfooding the platform for its own CMS and forum increases credibility that it can support real production use.
Built-in localization is valued by teams planning to serve multiple markets.
Areas for improvement
Collaboration capabilities are unclear, particularly simultaneous editing, version history, and branching.
Reviewers want proof that complex applications can scale and remain maintainable beyond an initial prototype.
Recovery and debugging workflows are unclear when AI-generated changes break an existing feature.
The level of developer control over infrastructure, custom configurations, integrations, and connectors is not clearly demonstrated.
Support for existing applications and flexibility in choosing underlying AI models are unclear.
7
Expertise AI
Expertise AI is where GTM experts monetize their playbooks as protected Al skills. Each expert gets a storefront where businesses demo and install these skills on a subscription, and gets paid every time one runs.
368103
7
Expertise AI
Expertise AI is where GTM experts monetize their playbooks as protected Al skills. Each expert gets a storefront where businesses demo and install these skills on a subscription, and gets paid every time one runs.
368
upvotes
103
comments
What users love
Protected skill boundaries keep expert playbooks hidden while allowing skills to use each customer's CRM, inbox, and other connected data.
Skills adapt at installation to a company's ICP, technology stack, and pipeline, producing context-specific outputs rather than generic templates.
Turns repeatable GTM judgment and workflows into executable skills, improving consistent results across a team.
Enables experts to monetize operational playbooks as recurring subscription or pay-per-run products instead of giving away static guides.
Practical cross-tool workflows, such as CRM plus email analysis and recurring campaign or stalled-deal diagnostics, reduce manual copying between tools.
Areas for improvement
No direct negative complaints were provided; reviewers raised unanswered questions about how custom skills are shared and which playbooks can be published.
Reviewers asked how protected skills are prevented from being reverse-engineered through repeated use or carefully designed prompts.
One reviewer noted that high usage could make a skill unprofitable unless gross profit per run is tracked alongside usage.
What users love
Protected skill boundaries keep expert playbooks hidden while allowing skills to use each customer's CRM, inbox, and other connected data.
Skills adapt at installation to a company's ICP, technology stack, and pipeline, producing context-specific outputs rather than generic templates.
Turns repeatable GTM judgment and workflows into executable skills, improving consistent results across a team.
Enables experts to monetize operational playbooks as recurring subscription or pay-per-run products instead of giving away static guides.
Practical cross-tool workflows, such as CRM plus email analysis and recurring campaign or stalled-deal diagnostics, reduce manual copying between tools.
Areas for improvement
No direct negative complaints were provided; reviewers raised unanswered questions about how custom skills are shared and which playbooks can be published.
Reviewers asked how protected skills are prevented from being reverse-engineered through repeated use or carefully designed prompts.
One reviewer noted that high usage could make a skill unprofitable unless gross profit per run is tracked alongside usage.
8
PageIndex
PageIndex gives you accurate, trustworthy answers across long, professional documents your work depends on. Bring in your entire document set, ask your hardest question, and click any citation to jump to the exact highlighted source line, so you can verify it in seconds.
36248
8
PageIndex
PageIndex gives you accurate, trustworthy answers across long, professional documents your work depends on. Bring in your entire document set, ask your hardest question, and click any citation to jump to the exact highlighted source line, so you can verify it in seconds.
362
upvotes
48
comments
What users love
Clickable exact-line citations let users verify answers quickly without leaving the chat.
Direct jumps to the relevant source passage reduce time spent scrolling through very long PDFs.
The product preserves context across consecutive follow-up questions.
Document-wide search and Q&A is viewed as especially useful for professional materials such as contracts, financial reports, research papers, and textbooks.
The document-first approach is valued because it keeps source material as the basis for answers.
Areas for improvement
No direct negative feedback was provided in the reviews.
Users raised unanswered questions about search latency.
Users asked how well it handles scanned or image-based documents.
Users asked whether it identifies the specific document version when duplicate, amended, or restated files exist.
Users asked whether cited answers can be shared via a link with colleagues who do not have an account.
What users love
Clickable exact-line citations let users verify answers quickly without leaving the chat.
Direct jumps to the relevant source passage reduce time spent scrolling through very long PDFs.
The product preserves context across consecutive follow-up questions.
Document-wide search and Q&A is viewed as especially useful for professional materials such as contracts, financial reports, research papers, and textbooks.
The document-first approach is valued because it keeps source material as the basis for answers.
Areas for improvement
No direct negative feedback was provided in the reviews.
Users raised unanswered questions about search latency.
Users asked how well it handles scanned or image-based documents.
Users asked whether it identifies the specific document version when duplicate, amended, or restated files exist.
Users asked whether cited answers can be shared via a link with colleagues who do not have an account.
9
1752vc Pitch Deck Analyzer
The Pitch Deck Analyzer gives you investor-grade feedback in minutes — trained on 25,000+ real decks and the investor decisions that followed. Upload yours and get slide-by-slide fundability feedback — stage-calibrated, checking narrative cohesion and cross-checking your claims for contradictions investors will catch. Know exactly where you lose conviction before you ever hit send. Built by 1752vc, a VC firm evaluating 4,000+ startups a year.
35288
9
1752vc Pitch Deck Analyzer
The Pitch Deck Analyzer gives you investor-grade feedback in minutes — trained on 25,000+ real decks and the investor decisions that followed. Upload yours and get slide-by-slide fundability feedback — stage-calibrated, checking narrative cohesion and cross-checking your claims for contradictions investors will catch. Know exactly where you lose conviction before you ever hit send. Built by 1752vc, a VC firm evaluating 4,000+ startups a year.
352
upvotes
88
comments
What users love
Stage-calibrated feedback accurately identified pre-seed issues, including missing technical-lead context and unsourced figures.
Slide-by-slide analysis surfaces missing information while accounting for what an early-stage company may not yet have.
Clear separation of critical fixes from quick wins makes deck revisions easier to prioritize.
The analyzer identifies deck blind spots and specific fixes that make the narrative read more strongly.
Recommendations can flag weak problem framing and other investor-relevant messaging issues.
Areas for improvement
Feedback comments would be more actionable with tailored example slides or sample wording based on the submitted deck.
Some users want API/MCP or open-source access so they can run custom agents and iterate beyond a one-time check-up.
One user reported unsolicited LinkedIn messages promoting the product, creating a negative impression of outreach.
What users love
Stage-calibrated feedback accurately identified pre-seed issues, including missing technical-lead context and unsourced figures.
Slide-by-slide analysis surfaces missing information while accounting for what an early-stage company may not yet have.
Clear separation of critical fixes from quick wins makes deck revisions easier to prioritize.
The analyzer identifies deck blind spots and specific fixes that make the narrative read more strongly.
Recommendations can flag weak problem framing and other investor-relevant messaging issues.
Areas for improvement
Feedback comments would be more actionable with tailored example slides or sample wording based on the submitted deck.
Some users want API/MCP or open-source access so they can run custom agents and iterate beyond a one-time check-up.
One user reported unsolicited LinkedIn messages promoting the product, creating a negative impression of outreach.
10
PostHog Desktop
A multiplayer workspace for you, your team, and your agents – with your product data as context, and PostHog tools to ship and measure. Build and edit your product | Run a fleet of agents | Turn product signals into PRs.
3513
10
PostHog Desktop
A multiplayer workspace for you, your team, and your agents – with your product data as context, and PostHog tools to ship and measure. Build and edit your product | Run a fleet of agents | Turn product signals into PRs.
351
upvotes
3
comments
What users love
AI-powered product editor positioned as a multiplayer workspace for product builders
Product context is retained, addressing AI coding sessions that start without context
Combines team collaboration and agent workflows in one workspace
Connects product data and PostHog tools to building, shipping, and measuring work
Areas for improvement
No negative feedback
What users love
AI-powered product editor positioned as a multiplayer workspace for product builders
Product context is retained, addressing AI coding sessions that start without context
Combines team collaboration and agent workflows in one workspace
Connects product data and PostHog tools to building, shipping, and measuring work
Areas for improvement
No negative feedback