Leni
AI platform that turns real estate teams' messy documents and siloed systems into verifiable underwriting, valuation, and portfolio reporting.
Overview
Leni is an agentic AI platform built for real estate and investment teams doing institutional-grade work: underwriting, valuation, portfolio and investor reporting, market research, and document extraction. Its pitch is that generic LLMs hallucinate too often for high-stakes financial decisions, so Leni layers a patent-pending "Routed-Knowledge Graph" (connecting a firm's own documents, emails, and systems like Entrata, ResMan, RealPage, and AppFolio) with a verification layer and human-approval workflow on top of whichever model you choose (Claude, GPT, Gemini, others). It cites independent-sounding benchmark scores, including 91.25% on SpreadsheetBench, 88.6% on GAIA, and 97% on its own "Bullshit Bench" for reducing false claims, all self-reported on its site.
Leni landed Product Hunt's #3 Product of the Day. Press coverage (Crunchbase, Yale SOM, York University's YFile, GS Futures/Medium) reports roughly $6.6M raised to date, including a seed round led by York IE with Second Century Ventures (the National Association of Realtors' fund) and Golden Section. That figure is press-reported, not a number Leni publishes on its own site.
Key Features
Routed-Knowledge Graph: Patent-pending tech connecting a firm's documents, emails, and systems (Entrata, ResMan, RealPage, AppFolio) into one private context graph.
Verification & Human Approval: A verification layer and human-approval workflow sit between model output and what you act on, aimed at reducing hallucinations.
Model-Agnostic: Works with Claude, GPT, Gemini, and other LLMs without locking you to one vendor.
Institutional Memory: Captures past decisions as structured traces in the organizational context graph.
Security-First: Containerized models hosted on Leni's own servers; no external data transmission, per its site.
Core Use Cases: Financial modeling and underwriting, reporting and asset management, investment memos and presentations, market research, document extraction, development and strategy.
Pricing
Starting price
Unconfirmed. leni.co publishes no pricing page (leni.co/pricing returns 404) and no pricing link in its navigation; access is via a "Talk to Sales" enterprise request or a "Try Now" self-serve onboarding flow, with no dollar amount disclosed for either.
Leni does not publish a pricing page: leni.co/pricing returns a 404, and there is no "Pricing" link anywhere in its navigation or footer. Access is offered two ways on the site: a "Try Now" self-serve onboarding flow (app.leni.co/onboarding) and a "Talk to Sales" enterprise request-demo form. Neither discloses a dollar amount, billing period, or whether the "Try Now" flow is genuinely free or requires payment details upfront.
Given its named enterprise customer base (Bozzuto, Greystar, CBRE, Colliers, Oxford Properties) and sales-led access model, this reads as a custom-quote enterprise product rather than a published self-serve price. Confirm directly with Leni before quoting a number.
Pros
Named enterprise customers (Bozzuto, Greystar, CBRE, Colliers, Oxford Properties) rather than vague social proof, a real signal of institutional traction.
Model-agnostic architecture avoids lock-in to a single LLM provider.
Purpose-built integrations with real estate systems of record (Entrata, ResMan, RealPage, AppFolio) rather than generic document upload.
An explicit verification and human-approval layer aimed at the accuracy problem that plagues generic LLMs in financial work.
Backed by real investors per press reporting: a seed round led by York IE with Second Century Ventures and Golden Section.
Cons
No pricing published anywhere on leni.co, not even a range; access requires "Talk to Sales" or a self-serve "Try Now" flow whose actual terms (trial length, whether payment is required, cost after trial) aren't disclosed on the site.
A narrow vertical tool, built specifically for real estate and investment teams doing underwriting and valuation work, not useful to most of this site's broader marketer, coder, and freelancer audience.
Its accuracy and benchmark claims (SpreadsheetBench, GAIA, Bullshit Bench scores) are Leni's own self-reported figures; no independent third-party audit of those numbers is visible on the site.
No affiliate or referral program of any kind is confirmed on the site.
The widely cited $6.6M funding figure comes from press reporting (Crunchbase, YFile, Medium), not Leni's own site, so treat it as reported rather than confirmed.
What Makes It Unique
Leni's differentiator is treating hallucination as an engineering problem rather than a prompting problem: its Routed-Knowledge Graph ties every answer back to a firm's actual documents and systems, with a verification-plus-human-approval layer between the model's output and what a user acts on. Staying model-agnostic instead of betting on one LLM vendor adds to that. The architecture is genuinely more accuracy-focused than most vertical AI tools, though the benchmark claims behind it are self-reported and unaudited.
Kay Score
6
/ 10
Tool Information
Pricing
Unconfirmed. leni.co publishes no pricing page (leni.co/pricing returns 404) and no pricing link in its navigation; access is via a "Talk to Sales" enterprise request or a "Try Now" self-serve onboarding flow, with no dollar amount disclosed for either.
Category
Finance & Accounting
Platform
Web / iOS / Android
Last Updated
