We've spent decades building infrastructure to protect what leaves our systems. Firewalls control outbound traffic. Data loss prevention tools scan what employees send. Egress policies govern which services can talk to the outside world. Encryption wraps everything in transit.
Now ask yourself: what infrastructure exists to understand what enters your system?
Not what blocks it. Not what stores it. What understands it — what it is, whether it's real, whether it belongs, whether it's safe, and how long it should stay.
The answer, for almost every company in the world, is: nothing. Data arrives, gets a superficial label check, and is treated as trusted from that moment forward. Your entire system — every database, every pipeline, every report, every downstream service — inherits that blind trust.
This is the most under-built layer in modern infrastructure. We built Uplint to change that.
Your infrastructure is content-blind
Here's something that should bother every engineer: your storage layer has no idea what it's storing.
S3 holds bytes. It doesn't know if those bytes form a 50-page PDF with zero readable words, a renamed executable masquerading as a document, or a restaurant receipt uploaded as a medical claim. It doesn't know and it can't know — because understanding content was never part of its job.
This blindness cascades. Every system that reads from that bucket inherits it. Your analytics pipeline counts blank documents as real submissions. Your compliance system logs empty files as received records. Your ML model trains on garbage data that passed every gate unchallenged. Your customer sees a "successfully uploaded" message for a file that contains nothing.
And it's not just about what's broken or empty. Consider a health insurance company that receives thousands of claim submissions daily. A user uploads a vacation selfie to the "medical claims" portal. The file is a valid JPEG. It's non-blank. It's under the size limit. It's not malicious. Every check in your pipeline passes. But it's the wrong content entirely — and no system in your stack can tell the difference between that selfie and a legitimate medical bill, because no system in your stack understands content.
This isn't a validation problem. It's an infrastructure problem. Your stack is content-blind, and no amount of extension checks, MIME type verification, or size limits will fix that, because none of those things look at what's inside the data.
The missing primitive: content intelligence
Every major infrastructure concern eventually gets its own layer. Networking got firewalls and load balancers. Authentication got identity providers. Observability got logging and tracing platforms. In each case, the pattern was the same: teams built ad-hoc solutions, realized the problem was universal, and the industry created a dedicated primitive.
Understanding incoming data is overdue for the same treatment.
We call this content intelligence — the ability to look beyond metadata and understand the substance of what's entering your system. It operates at three levels:
Structural truth. Is this data what it claims to be? Does the internal binary structure match the declared format? A file that says it's a PDF but has an executable header isn't confused — it's deceptive. Corrupt headers, polyglot files, format spoofing — structural intelligence catches what no label check can.
Substantive reality. Is there meaningful content inside? A PDF with zero readable words isn't a document — it's an empty shell. A spreadsheet with headers but zero data rows isn't a report — it's a template at best. An image that's a single solid color isn't a photo — it's nothing. These pass every traditional check, and they're everywhere. In regulated industries, they aren't just useless — they're a compliance risk that goes undetected until an audit.
Semantic context. Does this data belong where it was sent? This is the level that transforms what a trust layer can do. When your infrastructure understands content semantically, it can verify that a document uploaded to "insurance-claims" is actually a claim form, a prescription, or a medical bill — not a random receipt, not a personal photo, not someone's homework. Modern vision models and multimodal AI have made this feasible at API speed. Your infrastructure can now understand what data is, the way a human reviewer would — but on every submission, instantly.
No managed service offers this today. Every team that needs it builds it from scratch — partial solutions, duct-taped together, maintained by nobody. That's the gap.
Trust doesn't end at the gate
Most people think of data validation as a checkpoint: data arrives, you check it, it passes or fails. But real trust has a lifecycle.
If your infrastructure understands what entered your system — not just when — it unlocks capabilities that were previously impossible:
Intelligent retention. Regulated industries have strict rules about how long certain data must be stored. Medical records might require 7 years. Tax documents might require 10. Temporary uploads should be purged in weeks. But S3 lifecycle policies don't know what a file is — they know when it was created. They can't distinguish a medical claim that must be retained for a decade from a duplicate upload that should have been cleaned up last month. A trust layer that understands content can enforce retention based on what the data actually is, not just its timestamp.
Storage intelligence. Without content understanding, buckets grow forever. Files sit for years past their legal retention window — or get deleted too early, violating compliance. Monthly cloud bills climb because nobody can confidently say which data is safe to remove. When an auditor asks "why are you still storing this patient document from 2019?" — there's no good answer. Content intelligence turns your storage from a growing liability into a managed, compliant system.
Downstream trust propagation. When every piece of data that enters your system has been structurally verified, content-analyzed, and semantically classified, every downstream system inherits that trust. Your analytics are cleaner. Your ML models train on real data. Your compliance trail is airtight. Trust, once established at the boundary, compounds through your entire stack.
Introducing Uplint
Uplint is the trust layer for incoming data. It sits between the outside world and your infrastructure, and it ensures that every piece of data is understood, verified, and trusted before it enters your system.
One API call. The full trust pipeline.
const result = await uplint.validate(file, {
context: "medical-claims",
scan: true,
detectBlanks: true,
});
if (!result.trusted) {
// result.reasons: "blank_document" | "content_mismatch" | "threat_detected" | ...
}
That call triggers structural verification, content analysis, blank detection, semantic classification, threat scanning, and audit logging — as a single managed pipeline. Your code doesn't need to know how to detect a blank PDF, identify a renamed executable, or classify whether a document is a real medical claim. It asks one question: can I trust this data? Uplint answers it.
Every decision is logged with full context. Who sent what, when, what was verified, what was flagged, what was allowed through. Compliance-ready from the first request.
The vision: data intake as a cloud primitive
Every cloud has S3 for storage. Lambda for compute. SQS for queues. Cloudflare for network protection. But no cloud has a primitive for receiving and understanding external data.
We believe data intake should be a fundamental infrastructure layer — not something every team builds ad-hoc from a dozen stitched-together services.
Today, Uplint delivers the core trust pipeline: structural validation, content intelligence, blank detection, threat scanning, context-based rules, and audit logging.
Next, we're building AI-powered semantic validation — context-aware document classification, PII detection before data reaches storage, intelligent retention policies tied to content type, and auto-extraction of structured data from incoming documents.
The destination is the universal trust layer for any external data entering any system — files, API payloads, webhook data, email attachments, form submissions. Every SaaS app. Every enterprise. Every regulated industry.
We're building the Cloudflare for incoming data. Cloudflare protects your network boundary. Uplint protects your data boundary.
Experience it
The fastest way to understand what a trust layer does is to see your own data through its lens:
pip install uplint
uplint scan ./uploads
Thirty seconds, and you'll see what your infrastructure has been blind to — the blank documents, the structural anomalies, the content that shouldn't be there. Most teams are surprised by what they find.
The API brings the same intelligence to production, with context-based rules, semantic validation, and full audit logging. The free tier is the real product — not a trial.
We believe every system that accepts external data needs a trust layer. We believe content intelligence belongs in infrastructure, not in application code. And we believe that the way we handle incoming data today — blindly, superficially, without understanding — will look as primitive in five years as running a web application without a firewall looks today.
That's what we're building. Come see what your infrastructure has been missing.
Uplint is the trust layer for incoming data. Start building free →