AI software · Bordair
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Bordair
Real-time prompt injection protection for LLM applications across text, image, document, and audio.
Partner summary
The offer at a glance
A quick read on buyer fit, pitch, economics, and promotion fit.
Best buyer
AI product engineers shipping LLM features to production
Main outcome
Inline injection scanning under 50ms (p99 38ms) keeps AI features fast even with a security layer in front.
Commission
To be confirmed
Best channels
Developer-Focused Content And Tutorials, Technical Blog Posts And Integration Guides, AI Security Newsletters And Communities, Comparison And Review Content Vs Alternative Scanners
Terms
Bordair operates under UK GDPR and the Data Protection Act 2018 as a UK sole trader. Do not imply certifications beyond what is published. Avoid customer-named claims unless founder-supplied.
Main pitch
Position Bordair to engineers shipping LLM features as the drop-in guard for prompt injection: one API call covers text, image, document, and audio in under 50ms, with an output...
Economics
Partner terms
Commission, pricing model, and review timing for this listing.
Commercial terms
Partner terms
Founder confirmation required before partners promote this listing.
- Commission
- To be confirmed
- Pricing
- Subscription
- Duration
- —
- Review period
- 30 days
Pricing tiers
Free
Primary$0.00/ month
Tracks Self Serve Signup
- 200 scan credits per week
- 20 scans per minute
- All modalities available (text, image, document, audio)
- Standard detection model
Lite
$3.99/ month
Tracks Self Serve Subscription
- 1,500 scan credits per week
- 50 scans per minute
- Full multimodal scanning
- Castle Kingdom 5 unlocked
- Email support
Individual
$19.00/ month
Tracks Self Serve Subscription
- 10,000 scan credits per week
- 100 scans per minute
- Output scanning with custom regex rules
- All modalities
Business
$99.00/ month
Tracks Self Serve Subscription
- 100,000 scan credits per week
- 2,000 scans per minute
- 99.9% uptime SLA
- Priority routing and support
- Output scanning included
Enterprise
Custom/ custom
Tracks Contact Sales
- Unlimited rate limits
- Custom SLAs
- Dedicated support
- Semantic layer (coming soon)
Who this converts for
The buyers this offer is shaped for. Match your reach to the strongest audience fit.
AI product engineers shipping LLM features to production
Backend, full-stack, and AI engineers integrating LLMs into customer-facing products who need to harden user inputs against injection before launch.
Pain points
- User inputs can override system prompts and exfiltrate data
- Pattern matching misses semantic and multi-turn attacks
- Audio and document inputs bypass text-only filters
- Async or queued moderation breaks synchronous chat UX
- Prompt injection overrides system instructions and leaks data
- Regex and pattern matching miss semantic and multi-turn attacks
- File, image, and audio inputs bypass text-only filters
- Async or queued moderation breaks real-time LLM UX
- No standard control for OWASP LLM01 in AI feature reviews
Desired outcomes
- Block prompt injection inline without adding noticeable latency
- Cover text, image, document, and audio in one call
- Ship LLM features without writing a custom security layer
- Cover text, image, document, and audio in a single call
- Stop sensitive content from leaking in LLM responses
- Demonstrate AI security coverage to internal and external reviewers
Solo builders and founders shipping AI side projects
Indie developers and small AI startups running early production traffic who want injection protection without committing to enterprise pricing.
Pain points
- Free tiers run out quickly once a side project gets real traffic
- Higher-tier security plans feel like overkill for a single feature
- Have to choose between no protection and an enterprise contract
Desired outcomes
- Cheap, drop-in injection protection for a single AI feature
- Multimodal coverage without paying for full enterprise tier
- An upgrade path that grows with the side project
Security and platform teams owning AI risk
Application security, platform security, and AI governance leads responsible for reviewing and approving LLM-powered features inside their company.
Pain points
- No standard control for prompt injection in the SDLC
- AI features ship faster than security can review them
- Hard to evidence coverage of multimodal attack surface
- Regex and homegrown filters do not stand up to audit
Desired outcomes
- Provide engineering with an approved, drop-in injection control
- Demonstrate coverage of OWASP LLM01 to auditors
- Centralise input and output guarding across AI products
Engineering teams or technical founders shipping LLM-powered features to external users who need an inline
Stop prompt injection from reaching my LLM and stop sensitive content from leaking back to my users, without slowing down the product.
multimodal injection guard with a documented
Stop prompt injection from reaching my LLM and stop sensitive content from leaking back to my users, without slowing down the product.
low-retention data posture
Stop prompt injection from reaching my LLM and stop sensitive content from leaking back to my users, without slowing down the product.
Why partners convert here
When to pitch this, and the outcomes the buyer actually gets.
Use cases
- Block prompt injection in customer-facing AI chat
- Block prompt injection in customer-facing AI chat
- Scan documents, images, and audio uploaded to AI features
- Scan documents, images, and audio uploaded to AI features
- Stop sensitive content from leaking in LLM responses
- Stop sensitive content from leaking in LLM responses
- Defend agentic and multi-turn AI workflows
- Defend agentic and multi-turn AI workflows
Outcomes
Block prompt injection inline without adding noticeable latency
Cover text, image, document, and audio in a single call
Stop sensitive content from leaking in LLM responses
Demonstrate AI security coverage to internal and external reviewers
Sub-50ms inline scanning with p99 of 38ms
EvidenceMultimodal coverage in a single call
EvidenceDual-region EU and US deployment
EvidenceMulti-turn detection via conversation history
EvidenceOpen-source multimodal attack dataset
EvidenceBefore · After
Block prompt injection in customer-facing AI chat
Before
Attackers override system prompts, impersonate operators, and exfiltrate data through crafted chat messages, and regex filters miss the semantic patterns.
After
A single /scan call gates every user message, with a purpose-built detection model catching direct injection, jailbreaks, and authority impersonation.
Expected outcome: Production AI chat that refuses injection attempts inline while keeping conversational latency under 50ms of added scan time.
What makes this different
Where this offer beats the alternatives.
Inline sub-50ms scanning instead of async moderation
Multimodal coverage (text, image, document, audio) in one call
435M-parameter detection model purpose-built for prompt injection
Output guard with per-rule actions: block, redact, warn, log
Dual-region EU and US deployment with latency routing
Conversation-aware scanning for Crescendo and split-payload attacks
Open-source bordair-multimodal dataset and published comparison content
Promotion strategy
Partner playbook
Angles, questions, objections, and inputs to keep outreach sharp.
Value proposition
Real-time prompt injection protection for LLM applications across text, image, document, and audio.
How to pitch
Position Bordair to engineers shipping LLM features as the drop-in guard for prompt injection: one API call covers text, image, document, and audio in under 50ms, with an output guard for sensitive content on paid plans. Lead with the inline latency story and the 435M-parameter detection model, then point to the docs and the free tier for quick proof.
Positioning
The real-time, multimodal prompt injection API for production LLM applications - inline, sub-50ms, and built specifically for the attack surface rather than retrofitted from generic moderation tools.
Best angles to test
- Inline sub-50ms latency vs async moderation pipelines
- Multimodal coverage in one call vs stitching point tools
- Output guard for leaked keys and PII on paid plans
- Drop-in alternative to Lakera Guard, PromptGuard, Rebuff, and Vigil
- Free tier and $3.99 Lite plan as an easy upgrade for solo builders
- Real-time prompt injection protection for LLM applications
- Multimodal scanning across text, image, document, and audio in one call
- Sub-50ms inline scanning with stated p99 of 38ms
- Less than 0.1% false positive rate (per Bordair website)
- Dual-region EU and US deployment with latency-based routing
- Output scanning with custom regex rules on paid plans
- Drop-in API with Python and JavaScript SDKs
Angles to avoid
- Do not claim Bordair guarantees zero injection bypasses
- Do not claim specific customer logos or case studies unless founder-supplied
- Do not claim 100% uptime or SLA beyond what the published terms state
- Do not claim official partnerships with model providers or clouds
- Do not claim results are typical or guaranteed
- Do not claim Stripe-verified payouts or managed checkout readiness
Discovery questions
- Where in your product does user-controlled content reach an LLM?
- Which modalities do users send today - text only, or also files, images, audio?
- How are you handling prompt injection risk in your current AI features?
- Is your AI workflow single-shot or multi-turn and agentic?
- Do you have an output-side requirement to stop leaks of secrets or PII?
Disqualifiers
- Internal-only LLM tools with fully trusted inputs
- or buyers expecting an end-to-end AI governance suite beyond inline prompt injection scanning.
Target keywords
Objections & responses
“We can just write regex rules ourselves.”
Response: Regex catches the easy patterns but misses semantic attacks, multi-turn escalation, and cross-modal payloads. Bordair pairs a 435M-parameter detection model with regex-style output rules, so you get both layers without maintaining them in-house.
“Another inline call will slow our LLM down too much.”
Response: Bordair scans synchronously in the request path with a stated p99 of 38ms and sub-50ms inline target. There are no async queues or polling, and obvious attacks short-circuit before more expensive stages run.
“We only take text input, why pay for multimodal?”
Response: Start on the free or Lite tier with text-only scanning. The same API is ready when you add file uploads, voice, or RAG over user-supplied documents, so you do not have to swap vendors later.
“How do we know our prompts and user data are not retained?”
Response: Bordair stores only a one-way SHA-256 hash of input plus scan metadata, never the raw text, image, document, or audio. Retention and sub-processors are documented in the public privacy policy under UK GDPR.
“How does Bordair compare to Lakera, PromptGuard, Rebuff, or Vigil?”
Response: Bordair leans on multimodal coverage in one call, sub-50ms inline latency, and transparent pricing from a free tier upward. The Bordair blog publishes side-by-side comparison posts so technical buyers can evaluate on detection method, latency, and production readiness.
Rules
Promotion rules
Where you can promote, what is restricted, and what the founder requires.
Allowed channels
Restricted channels
- AI-generated content
- Yes
- Content reuse
- No
- Founder approval
- Yes
Approved claims
- Real-time prompt injection protection for LLM applications
- Multimodal scanning across text, image, document, and audio in one call
- Sub-50ms inline scanning with stated p99 of 38ms
- Less than 0.1% false positive rate (per Bordair website)
- Dual-region EU and US deployment with latency-based routing
- Output scanning with custom regex rules on paid plans
- Drop-in API with Python and JavaScript SDKs
Claims to avoid
- Do not claim Bordair guarantees zero injection bypasses
- Do not claim specific customer logos or case studies unless founder-supplied
- Do not claim 100% uptime or SLA beyond what the published terms state
- Do not claim official partnerships with model providers or clouds
- Do not claim results are typical or guaranteed
- Do not claim Stripe-verified payouts or managed checkout readiness
Compliance notes
- Bordair operates under UK GDPR and the Data Protection Act 2018 as a UK sole trader. Do not imply certifications beyond what is published. Avoid customer-named claims unless founder-supplied.
Evidence
Proof & trust signals
Claims, evidence links, and operational trust signals partners can lean on.
Proof points
- p99 scan latency: 38 ms
- modalities supported: 4 modalities
- false positive rate: 0.1 %
- regions: 2 regions
- attack categories: 18 categories
- Block prompt injection inline without adding noticeable latency
- Cover text, image, document, and audio in a single call
- Stop sensitive content from leaking in LLM responses
- Demonstrate AI security coverage to internal and external reviewers
- Sub-50ms inline scanning with p99 of 38ms
- Multimodal coverage in a single call
- Dual-region EU and US deployment
- Multi-turn detection via conversation history
- Open-source multimodal attack dataset
Proof links
- Bordair homepage
Product overview, live demo, threat coverage, and platform capabilities.
- Bordair API documentation
Quick start, authentication, rate limits, errors, and all /scan endpoints with Python and JavaScript SDK examples.
- Bordair blog
Prompt injection research, open-source dataset releases, and product updates.
About Bordair
Bordair is a drop-in API that scans every input to your LLM application for prompt injection in under 50ms. It covers four modalities in a single call, uses a 435M-parameter detection model purpose-built for prompt injection, and adds an output guard with custom regex rules to block, redact, or warn on sensitive content before responses reach users. Dual-region deployment in EU (London) and US (Virginia) keeps latency low for production AI products.
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Listing transparency
Company activation will confirm the remaining commercial and tracking details.