510(K) PREDICATE INTELLIGENCE · LIVE

Find your strongest 510(k) predicate in minutes.

AI-powered predicate analysis backed by 91K+ indexed 510(k) summaries, the full openFDA clearance history, FDA guidance documents, and semantic search. FDA Best Practices compliance scoring on every candidate.

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KEENR · 510(K) PREDICATE REPORT
v1

DEVICE · K-XXXXXX

Predicate Intelligence Report

Generated for review · 35+ pages

PART 1

Executive Summary

  • Recommended predicate
  • Pathway decision
PART 2

Selection Strategy

  • 91K+ semantic search
  • Lineage 3 levels deep
PART 3

Technical Evidence

  • 8-dimension SE matrix
  • Best Practices scorecard
PART 4

Submission Framework

  • Pathway + PCCP + eSTAR
  • Action checklist
Citation-linked · auditable PDF + Word (Partner)
WHO THIS IS FOR

Built for health-tech teams navigating FDA clearance.

PERSONA · 01

Startup founders

First 510(k) submission? Get expert-level predicate analysis in minutes, without a multi-week, $5,000+ engagement. Understand your regulatory landscape before you spend.

PERSONA · 02

Regulatory affairs

Validate predicate selection with data-driven scoring, FDA Best Practices compliance, and a drafted 510(k) Summary narrative to adapt against your evidence, whether you're doing the work in-house or working with an outside consultant. Save hours of manual research either way.

PERSONA · 03

Consultants & advisors

Deliver predicate analysis to your clients faster. Use Keenr as your research engine while you focus on strategy and client relationships. Partner plans add editable Word export and volume pricing.

PERSONA · 04

Investors & diligence teams

Evaluate regulatory feasibility in minutes. Understand pathway risk, predicate strength, and competitive landscape before committing capital. Same report your portfolio companies will use, ready to share.

HOW IT WORKS

From device description to regulatory strategy in 4 steps.

STEP 01

Describe your device

Enter your device description and intended use. Run Keenr's one-click input check to flag vague or contradictory wording before it costs you a report.

STEP 02

We search 91K+ clearances

Hybrid search combines openFDA structured data with semantic similarity across the full 510(k) summary corpus. Cross-code discovery finds predicates keyword search misses — even in product codes with zero prior clearances.

STEP 03

AI evaluates each candidate

Our reasoning loop scores every candidate against FDA's 4 Best Practices criteria, runs an 8-dimension substantial equivalence comparison aligned with eSTAR, and traces predicate lineage chains up to 3 levels deep.

STEP 04

Get your report

Download a 35+ page branded PDF with predicate recommendation, lineage chains, pathway decision, and a drafted 510(k) Summary narrative formatted per FDA guidance Section VI. AI/ML reports run longer with PCCP, foundation model, and algorithm change sections.

WHY KEENR

Not just a database search.

Most predicate tools sort by date. We rank by relevance to your device.

METHODOLOGY

FDA Best Practices aligned

Every predicate is scored against FDA's September 2023 guidance: well-established methods, safety performance, no unmitigated issues, no design-related recalls. You get a compliance scorecard, not just a list.

RETRIEVAL

Semantic search across 91K+ submissions

We don't just match product codes. Our vector database embeds every 510(k) summary and finds semantically similar devices across ALL product codes — catching predicates keyword search misses entirely.

EVIDENCE

Predicate lineage chains

See who your predicate cited as THEIR predicate, and who they cited. Trace citation chains 3 levels deep from actual 510(k) summary text. Understand chain depth and risk before FDA asks.

AI/ML DEPTH

AI/ML device depth, built in

Every AI/ML report includes software taxonomy (SaMD vs SiMD, locked vs adaptive), IMDRF risk classification, PCCP requirement assessment against 80+ cleared precedents, a weekly-refreshed foundation-model disclosure tracker, and algorithm-change precedents drawn from real cleared filings — grounded in FDA's January 2025 AI-Enabled Device Software Functions guidance.

PATHWAY ENGINE

Regulatory pathway decision engine

Not just "510(k)" — we evaluate Traditional, Special, Abbreviated, De Novo, Breakthrough Device, and PMA pathways with specific eligibility reasoning, PCCP assessment, and pre-submission meeting recommendations.

OUTPUT

Drafted 510(k) Summary narrative

Get a multi-paragraph predicate selection narrative formatted per FDA guidance Section VI. Explains predicate choice, best practices compliance, and substantial equivalence basis. Adapt it against your evidence.

EARLY-STAGE STRATEGY · RESEARCH OUTPUTS

What this report does for your submission.

Eleven research outputs across the five areas of a 510(k) — plus two more when your device is AI/ML. Early-stage strategy your team, your consultant, or your institutional partner can build a submission around.

Pathway decision

Traditional 510(k)SpecialAbbreviatedDe NovoBreakthroughPMA
Recommended · with reasoning → §2
REGULATORY PATHWAY STRATEGY

Accelerates Pathway Planning

A recommended pathway, with the reasoning shown.

Detail +Detail −

Recommends a regulatory pathway with the reasoning behind it, comparing Traditional, Special, and Abbreviated 510(k) against De Novo, Breakthrough Device, and PMA for your device profile. Gives your team or consultant a defensible starting point.

Tests Product Classification

An outright code call: one, a pair, or no clean fit.

Detail +Detail −

Tests whether the product code you're considering fits your device's technical features, surfaces adjacent codes worth a closer look, and makes an outright call: file under one code, a pair, or flag that no code fits cleanly yet. Reduces the risk of building a submission on a misclassified code.

Ranked candidates

  • K183927 0.94
  • K201432 0.93
  • K198567 0.89
100-pt Best Practices scale · scorecards visible
PREDICATE & MARKET INTELLIGENCE

Strengthens Predicate Selection

A scored shortlist — every candidate’s scorecard visible.

Detail +Detail −

Ranks predicate candidates on a 100-point scale using FDA's September 2023 Best Practices criteria. Produces a scored shortlist of the most defensible substantial-equivalence options, with the full scorecard visible for every candidate, ready for a regulatory consultant's review.

Strengthens Safety Vetting

Two safety lenses: your whole product code, then each candidate.

Detail +Detail −

Two safety lenses: aggregate adverse-event volume across your entire product code, plus a per-candidate MAUDE and recall deep dive linked straight into FDA's database. Surfaces safety patterns worth investigating before your team or consultant builds the substantial-equivalence argument.

Uncovers Competitive Insights

The clearance landscape, quantified.

Detail +Detail −

Quantifies the clearance landscape for your product code (volume, average review time, recent activity), and tracks semantically adjacent codes for competitive devices a keyword search might miss.

eSTAR mapping

  • §4 Device Description drafted
  • §5 Substantial Equivalence drafted
  • §9 Software Documentation outlined
  • §12 Performance Testing outlined
+ Section VI narrative · Pre-Sub packet
SUBMISSION DOCUMENTATION & TEMPLATES

Reduces Drafting Time

A Section VI narrative draft, ready to adapt.

Detail +Detail −

Produces a draft Predicate Selection Narrative aligned with FDA Section VI requirements. A working draft your team or consultant can adapt, not a finished submission.

Maps to eSTAR Template

Analysis routed to the eSTAR sections that need it.

Detail +Detail −

Routes the device analysis to mandatory eSTAR sections: Section 4 (Device Description), Section 5 (Substantial Equivalence), Section 9 (Software Documentation), Section 12 (Performance Testing). Cuts the translation work between research and template inputs.

Drafts Your Pre-Sub Question Packet

Q-Sub questions drafted before you meet FDA.

Detail +Detail −

When a pre-submission meeting is warranted, drafts device-specific Q-Sub questions with a similarities-and-differences scaffold and a high-level testing approach — a starting point your team or consultant can refine before meeting FDA.

Compliance read

  • Software documentation ENHANCED
  • IDE determination ASSESSED
  • Human factors FLAGGED
  • Bench testing STANDARDS-ANNOTATED
Prioritized launch checklist · §4
TESTING, COMPLIANCE & ROADMAPPING

Clarifies Compliance Needs

Documentation level and IDE flags, called early.

Detail +Detail −

Assesses whether your system likely requires the "Enhanced" software documentation level under FDA's guidance, and outlines the design specs, traceability matrices, and cybersecurity protocols reviewers typically expect. When clinical data is likely needed, it also flags whether an Investigational Device Exemption (IDE) is in play and at what risk category.

Informs Engineering Investment

A prioritized launch checklist.

Detail +Detail −

Produces a prioritized launch checklist: Pre-Submission meeting timing, multi-site validation with demographic stratification, human factors testing. Helps focus engineering and clinical investment on the work most likely to matter at FDA review.

Consolidates Regulatory Research

Your specialty panel’s guidance, linked in one place.

Detail +Detail −

Compiles the FDA guidance mapped to your device's medical-specialty panel — plus cross-cutting AI/ML, digital-health, and labeling guidance — each with a direct link and the specific requirements it raises for your submission.

PCCP intelligence

  • Training data
  • Model retraining
  • Performance specs
  • Deployment
Change-frequency across 80+ cleared PCCPs
AI/ML ALGORITHM LIFECYCLE MANAGEMENT Included when your device is AI/ML

Informs PCCP Strategy

A PCCP outline to develop with FDA.

Detail +Detail −

Drafts a Predetermined Change Control Plan (PCCP) outline your team or consultant can develop with FDA. Reduces the risk of the cycle where every post-market algorithm update triggers a new submission.

Anticipates AI/ML Review Risks

The failure patterns that trigger FDA questions.

Detail +Detail −

Surfaces recurring AI/ML failure patterns from cleared devices, with suggested mitigation areas for acceptance criteria and demographic dataset tracking. Anticipates the issues that most often trigger FDA additional-information requests.

PRICING · TRANSPARENT

Pay per report. Or by the bundle.

$499 per single report, with 3-pack and 10-pack bundles for teams running multiple devices. Partner plans add editable Word export and volume pricing.

See full pricing Start an analysis
REGULATORY REFERENCES

Built on FDA guidance.

The tool's predicate selection methodology is anchored in FDA's September 2023 "Best Practices for Selecting a Predicate Device" guidance, supported by the documents listed below. Every report cites the specific guidance informing each section.

FAQ

Frequently asked questions.

What is a 510(k) predicate device?
A 510(k) predicate device is a legally marketed device cited in a 510(k) submission to establish substantial equivalence. FDA requires that the predicate have the same intended use and similar technological characteristics, or different technology that does not raise different questions of safety and effectiveness. Predicate selection drives the entire submission: what testing FDA will expect, how performance is benchmarked, and how the device is positioned in the regulatory record. FDA's September 2023 “Best Practices for Selecting a Predicate Device” guidance defines the selection criteria — well-established methods, similar safety performance, no unmitigated use problems, no design-related recalls — that Keenr scores every candidate against.
How accurate is the predicate recommendation?
Our system searches 91K+ indexed 510(k) summaries plus the full openFDA clearance history using semantic similarity (not just product code matching) and evaluates candidates against FDA's own Best Practices guidance. Candidates are scored on intended-use alignment, technology similarity, and clearance recency, with weights tuned to FDA's 2023 Best Practices guidance — and the full scorecard is shown for every candidate in the report. Candidates that don't share your device's clinical function are dropped, and nothing below the relevance floor is shown.
What data sources do you use?
We combine three data sources: (1) openFDA REST API for real-time 510(k) clearance data, MAUDE adverse events, and recall records, (2) a vector database of 91,000+ extracted 510(k) summary texts, refreshed every two weeks (includes the boleary.com public corpus, CC BY 4.0), and (3) a predicate lineage graph built by extracting K-number citations from those summaries.
Can I use this for AI/ML medical devices?
Yes. Check the “AI/ML device” toggle in the input form and specify whether your algorithm is locked or continuously learning. The report will include IMDRF SaMD risk classification, PCCP requirement assessment, and AI/ML-specific documentation guidance based on FDA's January 2025 AI-Enabled Device Software Functions guidance.
How is this different from searching openFDA myself?
openFDA search by product code returns results sorted by date — the newest devices, not the most relevant. Our semantic search finds the best-matching predicates based on actual device descriptions, regardless of product code. We also add safety analysis, recall classification, lineage chains, and FDA Best Practices scoring that openFDA doesn't provide.
Is the report suitable for my 510(k) submission?
The report includes a Predicate Selection Narrative formatted per FDA guidance Section VI that can serve as a starting point for your 510(k) Summary. However, this is an AI-generated research tool — all content should be reviewed and adapted by a qualified regulatory professional before submission.
What does a Keenr report cost, and are there volume discounts?
A single Keenr Predicate Intelligence Report is $499. For teams running multiple devices, we offer a 3-report bundle at $1,299 ($433 per report, saves $198 vs. singles) and a 10-report bundle at $3,999 ($399 per report, saves $991 vs. singles). Bundle credits never expire. AI/ML-specific deliverables (PCCP Intelligence, foundation model disclosure assessment, algorithm change precedents) are included on every report at no additional cost. See the pricing page for full details, or email info@keenr.ai about Partner plans.
Do you offer consultant or multi-report plans?
Yes. Partner plans for consultancies and RA teams include an editable Word (.docx) version of every report, volume pricing, and team features. Email info@keenr.ai to set one up.
What if my device description isn’t good enough?
One click runs Keenr's input check on your device description and Intended Use text before the analysis spends a credit, flagging vagueness or contradictions that would weaken the report. Nonsense inputs are rejected outright, and the report echoes your exact submitted answers back, so a mismatch can't hide.
What if no predicate exists for my device?
The report says so honestly. Candidates that don't share your device's clinical function are dropped, and nothing below the relevance floor is padded in. If your classification is PMA-only, the report reframes accordingly — no forced 510(k) framing — and maps the closest PMA and De Novo approvals in your code family, with matched De Novo grant precedents for novel mechanisms.
How often is the database updated?
The 510(k) corpus refreshes every two weeks, the foundation-model tracker refreshes weekly, and openFDA data is queried in real time.
THE SAMPLE REPORT · FOUR REAL PAGES

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This tool is for informational and research purposes only and does not constitute regulatory, legal, or professional advice. All analysis is AI-generated and should be reviewed by a qualified regulatory professional. Data sourced from openFDA and publicly available 510(k) clearance packages. Terms · Privacy · FDA.gov

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