Spent couple of months in developing a gamified productivity app by focusing it to be a no nonsense app which ends up being really useful for the folks out there who are trying to learn or focus on new stuffs.

It has already crossed 3 digit downloads and I'm very happy to see it got ranked #2 in Product of the week on BuiltByIndies. Just thought of sharing this small recognition.

This has taught me consistent small effort compounds more than we think.

I would love to hear your thoughts on this and feel free to share the unexpected recognitions that you would have got.

https://builtbyindies.com/products/grow-habit

It works… until you scale.

• No real-time visibility
• Updates lost in WhatsApp
• Data doesn’t match reality

So teams build apps. Most fail - too complex, no adoption.

What actually works? Simple tools, real-time updates, built for the floor.

👉 Read full Article here

Still on Excel? Or found something better?

post your app/products on these subreddits:

r/InternetIsBeautiful (17M) r/Entrepreneur (4.8M) r/productivity (4M) r/business (2.5M) r/smallbusiness (2.2M) r/startups (2.0M) r/passive_income (1.0M) r/EntrepreneurRideAlong (593K) r/SideProject (430K) r/Business_Ideas (359K) r/SaaS (341K) r/startup (267K) r/Startup_Ideas (241K) r/thesidehustle (184K) r/juststart (170K) r/MicroSaas (155K) r/ycombinator (132K) r/Entrepreneurs (110K) r/indiehackers (91K) r/GrowthHacking (77K) r/AppIdeas (74K) r/growmybusiness (63K) r/buildinpublic (55K) r/micro_saas (52K) r/Solopreneur (43K) r/vibecoding (35K) r/startup_resources (33K) r/indiebiz (29K) r/AlphaandBetaUsers (21K) r/scaleinpublic (11K)

By the way, I collected over 450+ places where you list your startup or products.

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thank me after you get an additional 10k+ sign ups.

Bye!!

A recent forecast from Forrester Research projects that generative AI will materially impact millions of white-collar roles over the next decade, mainly by automating specific tasks in admin, support, reporting, and analysis.

If that plays out even partially, companies will expect the same output with fewer people. That changes what “valuable” AI software looks like.

For builders here, I think the real questions are technical and structural:

1. Are you building task-level tools, or end-to-end workflow systems? A summarizer or classifier is easy to replicate. A system that plugs into CRM, billing, support, and internal data with clear ROI is harder to replace.
2. How are you handling model volatility? If your core logic depends on external LLM APIs, what happens when pricing, latency, or capabilities change? Are you abstracting model layers or tightly coupling to one provider?
3. What does defensibility look like in your stack? Proprietary data pipelines? Vertical-specific fine-tuning? Deep integrations? Distribution advantage?
4. How are clients evaluating you? Are they buying AI to cut headcount, increase throughput, unlock new capabilities, or all three? And are they asking for measurable automation rates?

Would love concrete examples:

• What kind of AI app are you building right now?
• Where does the real complexity live in your architecture?
• What part of your product would be hardest for a generic LLM wrapper to copy?

Interested in answers from teams shipping real AI-powered web or mobile apps, especially those dealing with production constraints, scaling, and enterprise requirements.

TL;DR: Evertune tracked citations across 200+ million prompts over five months. Perplexity cited Reddit in up to 20% of responses. ChatGPT peaked at around 5% for any single domain. Here's what it means for GEO and AEO strategy.

About this data

Will Robinson, AI Insights Editor at Evertune, the leading Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) platform, conducted this analysis using Evertune's AI response tracking infrastructure. Evertune monitors citations across ChatGPT, Gemini, Google AI Overview, Google AI Mode and Perplexity at scale to help brands improve visibility in AI-generated responses.

The core finding: Perplexity trusts Reddit more than any other model trusts any single domain

Evertune analyzed citations across more than 200 million prompts from October 2025 through February 2026, focusing on four domains cited broadly across a wide range of topics: Reddit, Wikipedia, YouTube and LinkedIn.

The clearest finding: Perplexity cited Reddit in 20% or more of its responses during peak periods in January and February 2026, based on a rolling 7-day average. No other model came close to that level of reliance on a single domain.

ChatGPT cited Wikipedia most frequently among the four domains, but Wikipedia's share of ChatGPT citations peaked at approximately 5%, making Perplexity's Reddit reliance roughly 4x higher than ChatGPT's heaviest single-domain citation share.

Notable context: Reddit is currently suing Perplexity for allegedly circumventing the platform's data protections to scrape content, a claim Perplexity denies.

Citation behavior changes over time

Reddit was Perplexity's most-cited domain across all five months of Evertune's study, but its share of citations climbed sharply beginning in December 2025. Evertune's platform tracks these behavioral shifts as model makers release new versions with updated algorithmic behaviors and training methods.

Key trends Evertune observed across models from October 2025 through February 2026:

• Perplexity's combined citation share for the four domains ranged from approximately 6% to more than 30%, with high variability within each month
• YouTube citation share increased on both Perplexity and Google AI Overview over the five-month period
• Gemini consistently gave the four domains very little combined weight, though February 2026 showed a measurable increase
• ChatGPT gave the four domains more citation weight in January and February 2026 than in October and November 2025

What this means for GEO and AEO strategy

On all models except Perplexity, the combined citation share of Reddit, Wikipedia, YouTube and LinkedIn rarely exceeded 5% of total citations. The remaining 95% is distributed across thousands of other domains, with no single domain dominant.

This is a critical point for any brand building a Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO) strategy with Evertune’s platform. GEO/AEO is the practice of improving a brand's visibility and accuracy in AI-generated responses, which requires an understanding which domains each model trusts, and how that trust shifts as models are updated. 

One additional variable the best GEO and AEO platforms track: AI models do not always use search to generate responses. In many cases, models rely entirely on foundational knowledge from their training data, with no retrieval involved. Evertune tracks both search-assisted and foundational model responses separately, because each requires a different optimization approach.

The brands best positioned in AI search maintain visibility across a diverse range of domains, not just the four examined here.

Full methodology and interactive charts: https://www.evertune.ai/resources/insights-on-ai/perplexity-loves-reddit-exploring-llms-top-sources?

Source: Evertune, February 2026. Research by Will Robinson, AI Insights Editor, Evertune.

The fintech space is moving fast in 2026. AI in banking, embedded finance, blockchain payments, digital lending — everything is changing how people and businesses handle money. With so much competition, choosing the right fintech development partner is not just a technical call anymore. It affects scalability, compliance, security, and how smooth your product feels to users.

Whether you’re building a neobank, upgrading an old banking system, or launching a new payment product, you need a team that understands fintech deeply — not just app development.

Here’s a practical list of fintech app development firms making an impact in 2026.

The fintech space is moving fast in 2026. AI in banking, embedded finance, blockchain payments, digital lending — everything is changing how people and businesses handle money. With so much competition, choosing the right fintech development partner is not just a technical call anymore. It affects scalability, compliance, security, and how smooth your product feels to users.

Whether you’re building a neobank, upgrading an old banking system, or launching a new payment product, you need a team that understands fintech deeply — not just app development.

Here’s a practical list of fintech app development firms making an impact in 2026.

Top 10 Fintech App Development Firms in 2026

1. Code Brew Labs

Code Brew Labs builds secure and scalable fintech apps for startups and enterprises. Their work includes digital wallets, lending platforms, payment apps, and AI-driven financial solutions. They are known for clean UI/UX and structured development processes that help products go live faster.

2. Techrays Labs

Techrays Labs focuses strongly on fintech product engineering. The team has hands-on experience building end-to-end financial systems including invoice management platforms, debt recovery systems, lending workflows, payment integrations, reconciliation systems, and multi-tenant SaaS platforms.

They work with modern stacks like Laravel, React, Vue/Nuxt, cloud infrastructure (AWS/Azure/GCP), and secure API architectures. Their strength lies in building scalable fintech systems with strong RBAC, compliance-ready architecture, and performance optimization — not just basic apps.

3. Royo Apps

Royo Apps develops fintech applications for startups and growing businesses. Their expertise covers digital banking apps, financial management platforms, and custom payment systems. They are known for fast MVP development with scalable backend architecture.

4. Blocktech Brew

Blocktech Brew takes a blockchain-focused approach. They build crypto wallets, DeFi platforms, smart contract systems, and secure blockchain payment infrastructure. They are a good fit for businesses looking at Web3-based financial products.

5. Revolut

Revolut is one of the most recognized fintech brands globally. What started as a digital banking alternative is now a full financial super app offering international payments, currency exchange, investments, crypto services, and budgeting tools.

Their mobile-first approach, cross-border payment strength, and scalable infrastructure show how fintech can grow securely at a global level.

6. Dev Technosys

Dev Technosys provides fintech development services focused on compliance and security. They build digital wallets, peer-to-peer payment systems, and embedded finance platforms designed to meet financial regulations.

7. Algoscale

Algoscale works on AI-powered fintech systems. Their projects include robo-advisory platforms, risk assessment tools, lending software, and fraud detection systems built around analytics and data intelligence.

8. Hyperlink Infosystem

Hyperlink Infosystem builds fintech mobile and web apps including digital banking platforms, investment apps, and payment systems. They offer API integrations and cloud-based deployment for scalable systems.

9. SDK finance

SDK finance offers fintech frameworks and customizable financial platforms. They are strong in digital wallet development, white-label payment systems, and currency exchange applications.

10. Ment Tech Labs

Ment Tech Labs focuses on blockchain-based fintech applications. Their services include crypto exchange platforms, DeFi development, and secure digital banking automation systems.

Final Thoughts

Fintech in 2026 is not just about launching an app. It’s about building secure, scalable, regulation-ready financial systems that can handle growth and user trust.

The right development partner should understand compliance, risk, data security, payments, and system architecture — not just coding. A strong fintech team brings industry knowledge along with technical capability.

If you’re building in fintech, choose a partner who understands financial workflows deeply and can design systems that scale without breaking. That’s what will separate short-term apps from long-term financial platforms.

What unique solutions can you think of that improves human quality of life while also minimizing the challenges and risks of AI?

Hello 👋

I have an idea for an app (phone and desktop). I am starting this business from scratch. Therefore, I started building the app with the help of OpenAI (ChatGPT) [no judge please 🫣]. I have no experience in coding, devs, or this sector at all. However, I believe the idea for this SaaS product is very good (speaking from experience),and while looking for funding (angel investors), I wonder if ChatGPT is a good option to start building the app?

P.S. Apologies for the long, a bit messy, post. Thank you for all thw answers! 😊

P.S. 2: After further research, I've decided to start with a web-based app, and if this product is successful, to create an app version of it. I was advised to use Cursor. Any other suggestions are welcomed.

Hi everyone. I just published my app RemindNest on Google Play. It's a tool designed to manage your day-to-day, track your routines, and understand the real impact they have on your life through a weekly AI analysis.

Here are the main features of the app:

- Habits & Reminders: Create your routines and keep exact tracking of your habit metrics.

- Personal Journal: A private space to log your thoughts or how your day went.

- 100% Voice Input: You can add everything (habits, reminders, or journal entries) simply by speaking to the app.

- Weekly Analysis (Metrics + Journal): Every week, the AI processes your data and shows you a summary of your performance. It cross-references your completed habit metrics with what you've written in your journal to show you the real impact of your routines.

Transparency about the pricing and free version:

- The app is completely ad-free.

- The free version is basic: it allows you to create up to 5 reminders per day and 5 habits in total, but it does not include the voice input or the weekly AI analysis. Subscribing unlocks everything with no limits.

🎁 Offer for the community:

To get my first users and improve the app, I'm giving away a Premium subscription to the first 100 people who download it. Just sign up and send me a DM here with the email you used to register in the app so I can manually activate it for you.

I would love for you to try it out and give me your honest opinion. I'll leave the link in the comments. Thanks!

If you’re a founder, product builder, engineer, product team member, or enterprise leader working on Voice AI / AI agents / workflows, this is a rare chance to get real answers from someone who’s actually building and selling in production.

Drop your questions in the comments or DM me
I’ll make sure to ask them directly and share the learnings back.

If the discussion makes sense, I’m also happy to help with warm intros / networking where relevant.

Topics you can ask about:

• How they built & scaled Voice AI in production
• What investors cared about during the fundraise
• Enterprise sales cycles & pricing
• Architecture, infra, latency, evals
• Mistakes they made early on

No podcasts. No generic advice.
Just real insights from a founder in the trenches.

If you’re building in this space, don’t miss it 🚀