How AiDren compares
There are four ways to secure an LLM application: a self-serve security proxy such as AiDren, a self-serve detection API such as Lakera Guard, an enterprise AI-security platform such as Protect AI or HiddenLayer, or open-source libraries such as LLM Guard and ModelScan. They differ in coverage, integration effort and price, compared below.
Named products below are examples of each approach. Competitor facts on the head-to-head pages carry a source link and a last-checked date, because vendors get acquired and prices change.
The four approaches, side by side
| AiDrenAll-in-oneDrop-in proxy | Self-serve LLM-security toolsLakera, PromptGuard… | Enterprise AI-security platformsProtect AI, HiddenLayer… | Open-source / DIYLLM Guard, ModelScan… | |
|---|---|---|---|---|
| What it protects | ||||
| Prompt-injection & jailbreak blocking | ✓Yes | ✓Yes | ✓Yes | ✓Yes |
| Output & data-leak scanning | ✓System-prompt leaks, PII, secrets — redact or block | ~Varies by vendor | ✓Yes | ✓Yes, if you configure the output scanners |
| Malicious model-file scanning | ✓Six formats, from Hugging Face & GitHub | ~Rarely — injection-only, usually | ✓Yes | ✓Yes — a separate tool (ModelScan) |
| Agent egress / outbound-call monitoring | ✓Yes | –No | ~Some | –No — build it yourself |
| All six in one product | ✓Yes | –No — you combine several tools | ||
| Customization & collaboration | ||||
| Custom policy per key | ✓Term, regex, topic & threshold rules, per proxy key | ~Some — usually project-level, not per key | ✓Yes | ✓Yes, if you write the rules |
| Team accounts | ✓Unlimited seats, every plan, with an audit log | ~Depends on plan | ✓Yes | –You build your own auth |
| Getting started | ||||
| How you integrate | Change your base URL. One line. | Call an SDK / API from your code | SDK + guided onboarding | Self-host, then wire into every call |
| Time to first protection | ~5 minutes | An afternoon | Weeks (POC + procurement) | Days and up |
| Sales call required | ✓No | ✓No | –Yes | ✓No |
| Commercial | ||||
| Pricing | Public, flat £49 / £149 / £399 a month by tier, or yearly (2 months free) |
~$99–$499/mo, metered by request volume, then overage fees | Custom quote — contact sales | Free licence + engineering time |
| Monthly request allowance | ✓100k / 500k / 2M by tier (fair-use, not a hard wall), plus 10k top-ups | –Per tier, then metered overage | –Negotiated | Your infrastructure’s limits |
| Contract | Monthly or yearly, cancel anytime | Monthly | Annual | None |
| Operations & trust | ||||
| Prompts & responses stored | ✓No — decision metadata only | Varies by vendor | Varies — usually configurable | You decide |
| Hosting | UK / EU managed | Vendor SaaS | SaaS, or on-prem / private cloud | You host it |
| Ongoing maintenance | ✓None | ✓None | Low | –Ongoing — patching, tuning, updates |
| Deep compliance (SOC 2 / ISO 27001 / SIEM / SSO) | ~Partial — data minimisation; certifications not yet | ~Partial | ✓Yes | Build it yourself |
| Best fit | Teams shipping an AI feature now | One risk, moderate volume | Large org, deep compliance, procurement | Teams with security engineers and time |
✓ Covered / an advantage ~ Partial or varies – Not covered
The short version: only an enterprise platform matches AiDren across all six protections — and it’s sold on an annual contract, after a sales call. AiDren is the same coverage, self-serve and month to month.
Head-to-head, by name
Named comparisons against three specific tools — one from each category above.
AiDren vs Lakera
Self-serve runtime security vs Lakera Guard, whose acquisition by Check Point was announced in September 2025.
AiDren vs Protect AI
Six model formats plus injection, output & egress vs 35+ formats, enterprise-only.
AiDren vs LLM Guard
Hosted, drop-in proxy vs the open-source library you self-host and maintain.
Not marketing claims — the actual product
Real screens from a live AiDren account.
What each approach actually does
AiDren
One proxy. Public, flat pricing.
You point your app at AiDren instead of OpenAI, Anthropic or Mistral, one line of code. From then on it screens every request for prompt injection and jailbreaks, checks every response for system-prompt leaks and data leaks, scans model files (pickle, safetensors, GGUF, ONNX, joblib, Keras) pulled from Hugging Face or GitHub, applies any custom policy you attach to a key, and (optionally) watches your agent’s own outbound connections. Unlimited team seats on every plan. About 5 ms proxy overhead plus one screening call. Three public tiers: Starter £49/mo (100k checked requests), Growth £149/mo (500k), Scale £399/mo (2M). Every tier is the full product; pay monthly or yearly (2 months free). The request number is fair-use, not a hard wall. No sales call, cancel anytime.
Self-serve LLM-security tools
e.g. Lakera Guard (Starter / Pro), PromptGuard
An API or SDK you call from your own code to check a prompt or a response. Strong, focused prompt-injection and jailbreak detection with good latency. Priced by request volume — roughly $99–$499/month for 100k–1M calls, then pay-as-you-go overage. Usually injection-only: model-file scanning and egress monitoring are separate problems you solve elsewhere.
Enterprise AI-security platforms
e.g. Lakera (Enterprise), Protect AI, HiddenLayer, Prompt Security
Broad platforms: runtime firewall, model-supply-chain scanning, automated red teaming, posture management, SIEM and SSO integration, on-prem or private-cloud options, SLAs. Deep and compliance-ready. Sold through a sales team on annual contracts with custom pricing — built for large organisations with a dedicated security function and a procurement process.
Open-source / DIY
e.g. LLM Guard, NeMo Guardrails, ModelScan, Rebuff
Capable libraries you host and integrate yourself. Free to licence; the cost is engineering time — deploy them, wire them into every model call, tune the rules, keep them patched, and stitch injection screening, model-file scanning and egress monitoring into one coherent layer. Full control, no vendor, real ongoing effort.
When AiDren isn’t the right fit
We’d rather you picked the right tool. Choose something else if:
- You need the long tail of exotic formats — TensorFlow SavedModel, PMML, CoreML, TFLite — a dedicated model-scanning platform goes wider than our six.
- You need SOC 2 or ISO 27001 evidence now, a signed SLA, SIEM/SSO integration, or an on-prem deployment — an enterprise platform is built for that.
- You have security engineers and want full control with no third party in the request path — open source is the honest choice.
- Your volume is tens of millions of requests a month and you want volume pricing — talk to a metered vendor, or talk to us about a custom plan.
Frequently asked questions
What is the best prompt injection protection tool?
It depends on how you deploy. Teams that can send prompts to a hosted service and want one vendor for several protections often pick a hosted detection API or proxy. Teams with strict data-residency rules often run an open-source library such as LLM Guard themselves. Large enterprises with security teams often buy a platform. AiDren suits small teams who want proxy-level coverage, public pricing and no sales call.
Do I need a proxy at all?
Not necessarily. If you call one model from one service, an in-code library may be enough. A proxy helps when several services or agents share the same protection and you want one decision log.
When should I not use AiDren?
Choose something else if you need the long tail of exotic model formats, SOC 2 or ISO 27001 evidence now, a signed SLA, SIEM or SSO integration or on-prem deployment, full control with no third party in the request path, or tens of millions of requests a month with volume pricing.
See it for yourself
14-day free trial, no card. Live in five minutes. Plans from £49/month, cancel anytime.
Last checked 1 October 2026. See each head-to-head page for sources.
This comparison reflects our reading of publicly available information and each vendor’s own documentation as of August 2026. The four categories are generalisations — individual products differ, and pricing and features change often, so check the vendor directly before deciding. Named products are trademarks of their respective owners and are referenced here for identification and comparison only. Think we’ve got something wrong? Tell us and we’ll fix it: [email protected].