Leni is the most accurate and verifiable AI for serious investment work. Built on 21,000+ decision traces and processing 100M+ rows daily, it delivers finance-grade outputs with full auditability through source links, timestamps, and grounded comps. Leni outperforms GPT, Claude, and Manus on independent benchmarks for accuracy, modeling, and valuation while giving teams the trust they need when millions are on the line. Leni is part of Google Startups and a serious machine for investors.
Three years ago, we started with a simple observation:
The smartest people in investing were spending an absurd amount of time moving data between systems, fixing spreadsheets, validating reports, and checking the outputs of tools that were supposed to save them time.
Everyone was talking about AI.
But when real money was involved, most professionals still didn't trust it.
And honestly, they were right.
In high-stakes work, "mostly correct" isn't good enough.
A wrong number, a missed assumption, or a hallucinated fact can cost millions.
So instead of building another chatbot, we spent years working alongside sophisticated investors, operators, lenders, and asset managers to understand what trustworthy AI actually looks like.
Since then, we've supported more than $80B in assets, processed over 100 million rows of investment data every day, built proprietary verification systems, and tested relentlessly against real-world workflows.
The result is Leni.
THE most reliable and accurate AI infrastructure platform for investors and back office work that can analyze hundreds of files simultaneously, reason through complex tasks, validate its outputs, and deliver finished work instead of just generating responses.
In independent testing, Leni now ranks among the top AI systems for spreadsheet analysis, reasoning, and resistance to hallucinations. That work also led to our selection as one of the few companies invited to Google's Gemini Forum, where we've had the opportunity to collaborate with the DeepMind team.
But what excites me most isn't a benchmark result.
It's seeing professionals finally trust AI with the work that actually matters.
Huge thank you to our team, customers, advisors, investors, and everyone who helped us get here.
We’re excited to finally put Leni and its API portal into the hands of the broader Product Hunt community and see what you build with it.
We'll be here all day answering questions, gathering feedback, and learning from the community.
My team and I are here all day. Ask us anything 🙌
P.S. 🎁 Exclusive for the Product Hunt community: Try Leni.co directly on the platform or via APIs today with code PHLENI to get 90% off your 1st month's subscription on any plans, valid till the end of the day!
The combination of AI-powered research and clear source attribution is refreshing. Looking forward to seeing how investors and analysts incorporate this into their workflows.
Most AI tools help you find answers. Leni seems focused on helping users understand why those answers make sense. That distinction is incredibly important in investing. Great launch!
@arunabh_dastidar congrats on the launch! How well does this handle source data quality issues / discrepancies / missing data / disparate sources that tends to always appear in middle-market private M&A transactions? This is part of the automation puzzle I feel is the most difficult - it's whether the source data at the bottom is any good and how to efficiently correct it if it isn't
Hey Product Hunt 👋
I’m Zain, co-founder at Leni.
A lot of our work on Leni has come from sitting close to real investment and commercial real estate workflows and seeing where AI actually breaks.
It usually isn’t the final paragraph. It’s the step before it:
• Which rent roll did this number come from? • Did the model use the right NOI definition? • Why does the OM say one thing and the T12 another? • Is this based on the latest file, or the one someone uploaded two weeks ago? • Can this survive a partner review, lender question, IC memo, or investor update?
That is the bar we built around.
Leni helps investment and real estate teams move from scattered docs, spreadsheets, systems, and research into structured work products: underwriting support, market research, IC memos, portfolio reporting, diligence trackers, and source-backed answers.
The part I’m most proud of is that Leni is designed to slow down in the right places.
If the evidence conflicts, it should show the conflict. If the assumption is missing, it should ask. If a number is calculated, it should be reproducible. If a definition changes, the system should know which version was used. If the answer cannot be supported, it should say so.
That sounds less flashy than “instant AI answer,” but it’s what serious teams kept asking us for.
Commercial real estate teams taught us what accuracy really means in practice: numbers that tie back, assumptions that can be reviewed, sources that are easy to inspect, and outputs that hold up when real decisions are being made.
We delivered against that standard, and then pushed ourselves to take it further across spreadsheets, research, reporting, and multi-step workflows.
Excited to finally share Leni with the Product Hunt community today.
We’ll be here all day answering questions and learning from the feedback 🙌
P.S. Product Hunt community gets 90% off the first month with code PHLENI, valid today.
Very proud to see Leni launch today 🎉 Working with real estate and investment data has reinforced that accuracy starts long before analysis. Good data foundations make trusted answers possible, and it has been rewarding to contribute to that work.
Hallucinated figures are one of the top reasons that actually helpful platforms aren't adopted. Glad the Leni team has listened to the real estate and investment teams specifically to create something custom built and something you can trust in to give you dependable results every time.
Congrats on the launch today! 🍾
How does your “decision trace” and private context graph work over time—what gets stored, how do you prevent bad assumptions from becoming institutional memory, and how do you handle changing definitions (e.g., NOI, occupancy, same-store) across teams?
This is a strong space to build in, especially because Leni seems to sit close to real investment workflows like underwriting, portfolio reporting, market research, document review, and IC memo creation.
I was curious about the governance layer around this.
You already mention structured traces and an institutional context graph, which is interesting. How are you thinking about the human approval side of that trace?
For example, when an AI-generated underwriting note or market risk flag influences an investment memo, how do you capture who reviewed it, what assumptions they accepted, and why the team trusted that output at that point?
In investment workflows i feel like auditability feels less useful if it only shows source links, timestamps, and model history. The harder part is tracing the judgment around the decision.
Would love to understand how you are approaching this.
What are your subscription plans? Where can I find more information? I browsed through your site, but it wasn’t obvious.
Question: How do you validate that there was no hallucination at all? Do you show an audit trail back to the exact cells/files used or something?
Most "most accurate AI for finance" claims fall apart the moment you ask something that requires reasoning across multiple time periods or reconciling conflicting signals in the data. What's the actual benchmark here, accuracy against what baseline, on what types of queries? And I'm curious how Leni handles cases where the underlying data sources disagree, like when reported earnings differ across filings or analyst estimates conflict with management guidance.
Congrats for the launch tho
Congrats on the launch! 🎉
Curious — what was the biggest challenge in building an AI that investors can actually trust with high-stakes decisions? Was it the accuracy, the auditability, or getting users comfortable relying on AI for investment research? 👀
Looks like a really ambitious product. Wishing the team a successful launch day!
So true about the lack of trust. We tried a couple of AI document tools earlier this year and they completely lost the plot whenever a PDF layout wasn't perfectly clean or a spreadsheet had complex formulas. If Leni actually handles hundreds of files at once without breaking, it's going to save lean ops teams a ton of time. Love that you built a proper verification layer instead of another chatbot. Going to test this out today. Great work team..
Two things I'm curious about. The model-agnostic routing, how does Leni decide which LLM handles what? Is it task-based, like one model for number-crunching and another for writing memos, or something more dynamic? And does the user get any say in that or is it fully behind the scenes?
Also, as a founder myself, I'm curious how you got the first few institutional customers to actually trust AI with real money decisions. That's probably the hardest cold start problem in enterprise AI. Did you have to start with low-stakes work and earn your way up, or did one customer go all in early?
Arunabhcongrats on the launch! The accuracy-first framing really stands out. Most tools chase fluency and quietly hope the numbers are right, so flipping that order (retrieval and extraction before generation) feels like the correct instinct for finance. Curious how the verification layer handles a conflict - if two source documents disagree on a number, does Leni surface the discrepancy or resolve it for you?
Hello Product Hunt, excited to be live today with Leni. I'm Gaurav, co-founder at Leni.
Leni is an accuracy-first AI platform for investment finance and real estate teams. It helps you go from messy documents & siloed systems to structured, verifiable answers with analysis you can actually trust.
AI tools optimize for fluent responses. Leni obsesses over accuracy.
• With verification layers that validate outputs instead of "guessing." • Decision traces so you can see how an answer was formed and what it was grounded in • A context graph + Unified Data Model (UDM) that keeps information consistent across documents, models, and entities • A focus on retrieval + extraction (getting the right facts) before generation (writing the response)
If you work in investments, asset management, credit, capital markets, valuation, or any workflow where a single wrong number can derail a deal, Leni is for you.
Over the years, especially in the last 6 months, it's been rewarding to see skeptics become believers. Teams that started with us as an experiment now rely on Leni for mission-critical work. That trust came from obsessing over accuracy, building robust verification systems, and learning through real implementations.
We'd love feedback from the Product Hunt community:
What workflow are you trying to make "AI-native" today?
Where do existing tools break down on trust/accuracy?
Thanks to our customers, team, advisors, investors, and early supporters who believed in us before this became obvious.
We're here all day so fire away with questions 🙌
P.S. 🎁 Exclusive for the Product Hunt community: Try Leni.co directly on the platform or via APIs today with code PHLENI to get 90% off your 1st month's subscription on any plans, valid till the end of the day!
Hey PH fam 👋
I've been watching AI stumble in high-stakes professional work for a while now. Real estate and investment teams can't afford hallucinated numbers in an underwriting model or a memo that cites something that doesn't exist. The cost of that mistake isn't a slap on the wrist. It's a blown deal.
That's the exact problem Leni was built to solve.
Leni is an AI agent built specifically for real estate and investment teams. Not a general-purpose chatbot pointed at your files. A purpose-built system designed to handle the kind of work where accuracy is non-negotiable.
Here's what makes it different:
🏗 It connects to the actual systems your team already uses. Yardi, Entrata, RealPage, AppFolio, ResMan and more. No manual data wrangling. No explaining your world from scratch every time.
🔍 It doesn't just generate. It verifies. Multi-agent architecture cross-checks work and reduces hallucinations before anything lands in your hands.
📊 It delivers finished work products. Underwriting models, IC memos, lease abstracts, market research with cited sources. Not a 25-message thread you have to babysit.
🔐 It's built for sensitive data. Containerized models, strong guardrails, and a private institutional context graph that gets smarter about your firm over time.
And it's model-agnostic. Use your favorite LLM or let Leni route across models automatically for the best output. You're not locked into one model's limitations.
For anyone who's been burned by AI that sounds confident but gets the numbers wrong, this one's worth a serious look.
Big respect to @arunabh_dastidar and the Leni team for tackling one of the hardest problems in enterprise AI: not just being smart, but being trustworthy.
Check it out and drop your questions below!
Love the positioning. In investing, accuracy matters more than speed alone. A wrong model or uncited assumption can cost real money. Turning scattered docs into verified, cited memos feels like the right workflow for investment teams.
What’s the strongest early use case so far: acquisition memos, underwriting models, or portfolio reporting?
About Leni on Product Hunt
“The world’s most accurate AI for investors”
Leni launched on Product Hunt on June 5th, 2026 and earned 418 upvotes and 62 comments, earning #1 Product of the Day. Leni is the most accurate and verifiable AI for serious investment work. Built on 21,000+ decision traces and processing 100M+ rows daily, it delivers finance-grade outputs with full auditability through source links, timestamps, and grounded comps. Leni outperforms GPT, Claude, and Manus on independent benchmarks for accuracy, modeling, and valuation while giving teams the trust they need when millions are on the line. Leni is part of Google Startups and a serious machine for investors.
Leni was featured in Investing (26.6k followers), Artificial Intelligence (470.2k followers) and Data & Analytics (5.6k followers) on Product Hunt. Together, these topics include over 107.7k products, making this a competitive space to launch in.
Who hunted Leni?
Leni was hunted by KP. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Leni stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
KP
Hey Product Hunt 👋
I’m Arunabh, Co-Founder & CEO of Leni.
Three years ago, we started with a simple observation:
The smartest people in investing were spending an absurd amount of time moving data between systems, fixing spreadsheets, validating reports, and checking the outputs of tools that were supposed to save them time.
Everyone was talking about AI.
But when real money was involved, most professionals still didn't trust it.
And honestly, they were right.
In high-stakes work, "mostly correct" isn't good enough.
A wrong number, a missed assumption, or a hallucinated fact can cost millions.
So instead of building another chatbot, we spent years working alongside sophisticated investors, operators, lenders, and asset managers to understand what trustworthy AI actually looks like.
Since then, we've supported more than $80B in assets, processed over 100 million rows of investment data every day, built proprietary verification systems, and tested relentlessly against real-world workflows.
The result is Leni.
THE most reliable and accurate AI infrastructure platform for investors and back office work that can analyze hundreds of files simultaneously, reason through complex tasks, validate its outputs, and deliver finished work instead of just generating responses.
In independent testing, Leni now ranks among the top AI systems for spreadsheet analysis, reasoning, and resistance to hallucinations. That work also led to our selection as one of the few companies invited to Google's Gemini Forum, where we've had the opportunity to collaborate with the DeepMind team.
But what excites me most isn't a benchmark result.
It's seeing professionals finally trust AI with the work that actually matters.
Huge thank you to our team, customers, advisors, investors, and everyone who helped us get here.
We’re excited to finally put Leni and its API portal into the hands of the broader Product Hunt community and see what you build with it.
We'll be here all day answering questions, gathering feedback, and learning from the community.
My team and I are here all day. Ask us anything 🙌
P.S. 🎁 Exclusive for the Product Hunt community: Try Leni.co directly on the platform or via APIs today with code PHLENI to get 90% off your 1st month's subscription on any plans, valid till the end of the day!