Compare · Glyphward vs Lakera Guard

Glyphward vs Lakera Guard

Lakera Guard is the most recognisable name in prompt-injection defence and, in our honest read of the market, the strongest pure-text guardrail available today. Glyphward does not try to replace it. We were built for a different shape of attack — payloads hidden inside images and audio that walk past any text-first scanner — and sold through a different door: self-serve at $29/mo, with a free tier for benchmarking.

TL;DR

If your attack surface is LLM text I/O (chat, RAG, code assistants) and you have enterprise procurement, use Lakera. If your attack surface is user-uploaded images or audio (avatar SaaS, voice agents, screenshot-reading agents, multimodal chat), and you want a credit-card scanner with a free tier, use Glyphward. Mixed surface and a budget? Run both — they compose, Lakera on the text path, Glyphward on the upload path.

What each product actually does

Lakera Guard is a guardrail platform wrapping prompts and completions sent to LLMs. Its strengths are text prompt-injection detection, jailbreak filtering, PII detection, and content policy controls. Lakera’s public materials describe multimodal coverage — notably text-in-image detection — and the team has published research on multimodal PI. Their corpus is significant, seeded in part by the Gandalf project and hardened by enterprise customer traffic.

Glyphward is a single-purpose multimodal PI scanner. We do not try to be a general guardrail. We take an image or audio file and return a 0–100 risk score plus flagged regions on offending pixels or waveform windows. Our image pipeline is CLIP visual embedding + Tesseract OCR + a small text-in-image head, benchmarked against a curated FigStep and AgentTypo corpus. Our audio pipeline combines a waveform anomaly classifier with a Whisper-small transcript filter to catch WhisperInject-class payloads.

Honest feature table

	Lakera Guard	Glyphward
Text PI detection	Excellent — core product	Not a target surface; use Lakera or LLM Guard
Image PI (typographic)	Text-in-image extraction available	OCR + CLIP + text-in-image ensemble
Audio PI (WhisperInject)	Limited per public docs	Two-signal waveform + transcript ensemble
Bounding boxes on offending regions	Not advertised	Yes — pixels and waveform windows
Free tier	Community / trial historically	10 scans/day, no card
Self-serve entry price	~$99+/mo, enterprise gated above	$29/mo Pro, $99/mo Team
Buyer motion	Enterprise procurement	Credit card, self-serve
SSO, SOC 2	Yes	SSO-lite Team tier; SOC 2 on roadmap

The story underneath the table: Lakera’s roots are text PI and that is their strength; Glyphward’s roots are pixels and waveforms. Neither product eats the other’s lunch.

Where Glyphward wins

Multimodal coverage as a first-class product, not a roadmap item. Our image and audio pipelines are what you pay for. If a FigStep-style payload or WhisperInject-class waveform is the threat, we are the scanner built for exactly that.
Self-serve pricing for SMB AI builders. $29/mo Pro replaces three weeks of procurement. Free tier lets you benchmark before you commit.
Free public scanner as a benchmark. Paste an image, drop an audio clip — see what we flag. No contract, no demo call.

Where Lakera wins

Pure text prompt injection. Their text PI corpus, guardrail policy engine, and reporting are more mature than ours and mature than any text-PI product we know of.
Enterprise posture. SOC 2, SSO, audit trail, and the kind of security review paperwork a bank’s vendor-management team wants.
One platform for a broad guardrail suite. If you also need jailbreak filtering, PII redaction, and toxic-content controls on the same text path, Lakera gives you one invoice for all of it.

When to pick which

Pick Lakera if your dominant surface is raw LLM text I/O and you have an enterprise budget. You will not regret it.

Pick Glyphward if you ship a product that accepts image or audio uploads from end users, you have a self-serve budget, and you want a scanner that is specifically hardened against the attack classes text-first tools miss.

Run both if you have a mixed surface and the budget for it. Route text through Lakera; route uploads through Glyphward before they hit your vision or audio model. We publish integration recipes for exactly this pattern — see our free-tier API docs.

Migration and complementary deployment notes

Adding Glyphward next to Lakera is a one-endpoint change: route image or audio uploads to POST /v1/scan on Glyphward before they reach your downstream model, block or flag on the risk score, and keep Lakera untouched on the text path. No data migration, no exclusive vendor contract to renegotiate.

Moving fully off Lakera onto Glyphward is not a recipe we recommend unless your surface is genuinely upload-only. Our v1 is multimodal-focused; we do not pretend to replace a text PI detector.

FAQ

Is Glyphward affiliated with Lakera or Check Point?

No. Glyphward is independent. This page reflects public marketing and reporting as of April 2026 and does not represent Lakera’s current position — see lakera.ai for their own product claims.

Did the Check Point acquisition change anything for self-serve Lakera customers?

Per public reporting on the Sept–Nov 2025 acquisition, security-platform M&A typically shifts acquired products upmarket. Lakera may or may not publish changes to their self-serve tier — that is their announcement to make. What we can say is that we see an increase in inbound interest from SMB teams looking for self-serve multimodal coverage.

Can Lakera scan uploaded images today?

Their public product pages describe multimodal coverage with an emphasis on text-in-image detection. Treat any vendor claim, including ours, the way you would any security datasheet: run your own samples through both scanners and read the confusion matrix. Our free tier exists for that benchmark.

What about audio prompt injection?

Audio PI is not a first-class Lakera feature per their public docs at the time of writing. Glyphward’s audio pipeline is two independent signals — a waveform anomaly classifier plus a Whisper-small transcript filter — combined to catch WhisperInject-class attacks.