u/Most_Cardiologist313

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

https://preview.redd.it/xkjr0shfditg1.png?width=1919&format=png&auto=webp&s=13c9c3c40b8445477c85aa01119b7e1b3a79c1c2

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

https://preview.redd.it/0hjvjnl8ditg1.png?width=1919&format=png&auto=webp&s=ea1b3edfe12ad8413aa1597d73f2b0bb48fc80b8

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

https://preview.redd.it/m7xjkryf9itg1.png?width=1919&format=png&auto=webp&s=321dd22bdbee27959dcce5b0a1e66c3923fd36b5

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

https://preview.redd.it/kbsdw4b77itg1.png?width=1919&format=png&auto=webp&s=252d6bb91849d3ed20d36d3757e125774c31c5f9

Zentra construction, week 1 completed.

My observation: analysts at fintech startups keep asking the same questions regarding finances all the time. Revenue report, transactions, profit margin? Every single time they ask, someone has to go into the database to find the answers.

How about making the system smarter?

I built a solution that uses Claude AI to give answers to financial data questions in natural language. However, there's one important feature: the system learns! So, when the user asks "How much was our Q1 revenue?" right now, he receives the answer, while tomorrow he gets the exact same answer from memory under 50 milliseconds!

This week I worked on developing the engine. The engine connects to your database (reads only), however, the user does not interact with the database – he interacts with the engine, which is intelligent enough to remember everything.

However, the caching layer is the true game changer. While most other solutions recreate an answer each time, consuming all of your API costs, we cache everything! Your database updates only when it needs to, but we know which data is fresh and which one has become stale. Fast, accurate, and saving on AI API costs!

It's week 1 of much more to come. Currently, we have implemented only the backend part of it. The UI will go live next week.

Any suggestions are appreciated!

Hey everyone,

I’m currently building a SaaS MVP and ran into a domain issue. Most of the usual options like .com, .in, or .app were either already taken or priced way higher than what makes sense at this stage. I ended up finding a .live domain on Namecheap, and even after checking platforms like Hostinger and GoDaddy, it was the same situation everywhere — either unavailable or too expensive.

I’m trying to move fast and just get the product out (also need a domain for payment gateway verification), but I keep wondering how this might come across to users. If you landed on a SaaS product using a .live domain, would it affect how much you trust it, or would you not really care as long as everything else looks legit?

Would love to hear honest thoughts from people here.