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The patent experience is broken — so we reinvented it

End-to-end patent filing, built for startups that move fast.

01

Does protecting your idea feel harder than inventing it?

02
The Problem

That's because the patent system wasn't built for startups.

Cost

Patent costs are unpredictable, opaque, and always higher than expected.

Process

The process is convoluted + your attorney isn't always the best guide through it.

Strategy

Patent strategy feels intangible and falls behind the pace of your innovation.

Time

Coordinating calls, long lead times, and endless review cycles drain momentum when speed matters most.

03
Introducing Patentext

AI-assisted strategy and drafting.
Human-in-the-loop oversight.
Simple pricing. Days, not months.

04
Why Patentext

Patentext solves all the common challenges founders face

FIG. 1

Transparent pricing with cost projections you can plan around.

1x

A centralized dashboard and AI agents that know your portfolio keep next steps clear.

FIG. 3

Visual strategy maps you can actually understand, kept current by AI as your tech evolves.

FIG. 4

AI-powered async collaboration between your team and a dedicated patent agent.

05
Inside the Platform

The only end-to-end patent filing service built for startups that move fast.

How do we file in days for a fraction of the cost while others take months? Here's what's under the hood.

01

Capture ideas from your existing tools

Patentext works with your document management system and messaging apps, including Slack, Teams, Discord, and Google Chat, to extract potentially patentable ideas in real time, so your patent strategy never falls behind your innovation.

patentext — integrations
Channels
# general
# design
# engineering 2
# product
# research
Apps
Patentext
# engineering
AR
Anika Rao10:42 AM
got the new caching layer working — we're using a predictive invalidation approach based on user behavior patterns instead of TTL. reduced p99 latency by 68%
JK
James Kim10:44 AM
wait, that's a really novel approach. the behavior-pattern prediction for cache invalidation — is anyone else doing this?
Patentext10:44 AM
I noticed a potentially patentable concept in this conversation.
◆ Patentable Concept Detected
ConceptPredictive cache invalidation via user behavior modeling
Novelty Confidence 82%
Source#engineering — 10:42 AM
Add to Strategy Dismiss
02

Evaluate and prioritize every concept

A synthesized, easy-to-understand view of current and future applications, with automatic technical maturity, prior art, and business relevance evaluation for every identified concept.

patentext — strategy
All Concepts Ready to File Monitoring
▼ Priority ▼ Source ⟳ Updated 2m ago
Concepts Identified
24
+3 this week
Ready to File
6
+1 new
Avg. Novelty Score
78%
— stable
Active Filings
3
in progress
ConceptTech MaturityPrior Art RiskBusiness ValueStatus
Predictive cache invalidation High Low 9.2 Ready to File
Adaptive ML pipeline routing High Medium 8.7 Under Review
Context-aware API throttling Medium Low 7.4 Ready to File
Distributed graph consensus Early High 6.8 Monitoring
03

Draft applications with AI assistance

Purpose-built AI agents assist with disclosure, review, and filing when you're ready to move forward with a patent application, handling the heavy lifting so you can focus on building.

patentext — disclosure agent
Filing Workflow
Business Context
completed
Known Prior Art
14 refs reviewed
Technical Disclosure
in progress
4
Drafting In Progress
pending
5
Inventor Review
pending
6
Filing with USPTO
pending
D
Disclosure AgentActive
I've analyzed the predictive cache invalidation concept and the 14 prior art references. I've identified 3 novel aspects that differentiate your approach. Let me draft the technical disclosure — I'll need a few details from you.
Q1: The behavior prediction model — does it use real-time session data, historical patterns, or both?
Both — we build a baseline from historical access patterns, then adjust predictions in real-time based on the current session's behavior signals.
That makes sense, here's my understanding of how the behavioral prediction model works:
Generated — Concept Subgraph
User Behavior Signals Real-Time Session Analyzer Historical Access Logs Access Pattern Modeler Prediction Engine Staleness Score per cache entry Proactive Invalidation Signal session baseline out out
Refine this section, or ask me another question...
04

Review every detail with a human expert

A human expert manages higher-level strategic decision making and ensures legal and technical accuracy, reviewing every claim, every reference, every filing.

patentext — agent review
Predictive Cache Invalidation — Claims Draft
◉ Under Review
Claim 1 (Independent)
A computer-implemented method for predictive cache invalidation in a distributed computing environment, the method comprising: (a) maintaining a historical access pattern model derived from aggregate user interaction data across a plurality of cache entries; (b) monitoring real-time behavioral signals from an active user session to generate a session-specific prediction vector; (c) combining the historical access pattern model with the session-specific prediction vector to compute a staleness probability score for each cache entry; (d) proactively invalidating cache entries whose staleness probability score exceeds a dynamically adjusted threshold
SL
Sarah Levine
Patent Agent • 12 years exp.
Re: Claim 1(a) — "historical access pattern model"
Suggest narrowing this to specify the model type. "Aggregate" is broad — if you can cite the specific ML approach, it strengthens differentiation from US10,234,567.
AcceptModify
Re: Claim 1(c) — "staleness probability score"
This is strong novel language. I'd recommend adding a dependent claim for the threshold adjustment mechanism — it's another layer of protection.
AcceptModify
Review Checklist
Prior art differentiation verified
Claim scope appropriate
§101 eligibility confirmed
Dependent claims complete
Drawings specification finalized
05

Track your entire portfolio

Always know where things stand. Track every application from filing through prosecution with a visual timeline that keeps your entire team in the loop.

patentext — portfolio
Patent Portfolio — Acme Labs
TimelineListAnalytics
JanFebMarAprMayJunJulAug
Predictive Cache Invalidation
PTX-2025-007 • Provisional
Drafted
Reviewed
Filed ✓
Pending at USPTO
Adaptive ML Pipeline Routing
PTX-2025-006 • Non-Provisional
Filed
Pending at USPTO
Expected 1st action
Context-Aware API Throttling
PTX-2025-008 • Provisional
Drafted
Reviewed
Filed ✓
Pending at USPTO
Real-Time Anomaly Clustering
PTX-2024-003 • Non-Provisional
Filed
Pending
Office action
Responded
Expected 2nd action
Decentralized Auth Protocol
PTX-2024-001 • Granted
US 12,345,678 — Granted ✓
Drafting Under Review Planned Filed Pending Granted
"
I've been genuinely impressed with Patentext. The system's ability to form a coherent, structured understanding of an invention from imperfect source material stands out.
Michael Faibisch
Innovation First IP
0+
startups on the waitlist
0+
patents drafted on Patentext
0+
patents filed by the team
06
The Team

Built by people who
know patents.

Alex Flake

Alex Flake

CEO

300+ patents filed. Owns a patent agency. Harvey Mudd.

Marcus Virginia

Marcus Virginia

CTO

2x technical founder. University of Minnesota.

Alex Wilson

Alex Wilson

Founding Engineer

AI researcher. Caltech.

Robert Sachs

Robert Sachs

Strategic Advisor

30+ years in patent law. Yale Law School. Ex-big law.

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on the list.

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