Constellation Gate AI

Prompt injection and token savings - #1 in benchmarks

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Artificial Intelligence

Security

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genuine question on the "blockchain-anchored" audit trail claim - what does the blockchain actually buy you over a plain signed hash chain (like a Merkle tree you publish periodically)? tamper-evidence works fine with either, and blockchain usually only earns its cost when multiple mutually-distrusting parties need to verify something without a shared authority. for an audit trail that's presumably verified by the org itself or an auditor they already trust, that bar seems higher than what's needed here, unless I'm missing what it adds

"#1 across 16 public prompt-injection datasets" is a strong claim - is that benchmark run by you internally or is there a third party leaderboard I can check that number against? also the 20-40% token savings "without changing model output" - does the compression step ever get caught out by a prompt that relies on exact wording (like a few-shot example)

How does the immutable audit trail actually work in practice, is there a per-call cost or does it come bundled with the free tier?

Combining prompt injection protection with token optimization is an interesting mix since people usually think about those separately. Have you found that customers come for the security side first, or are the benchmark results what usually gets their attention?

Curious what the benchmark setup looks like: are you measuring against known jailbreak/prompt injection datasets, real agent workflows, or synthetic prompts? Also wondering whether the token savings come from prompt compression, routing, filtering, or something else under the hood.

Hi! I'm Gabriel, and I'm also part of the engineering team behind Gate AI. I just wanted to add that we're heavy users of Gate AI ourselves. The token savings and the injection protection do make a difference.

Hey everyone! I’m Marcus Sousa, a Software Engineer at Constellation Network.

Over the past few months, I’ve been helping build Gate AI, and it’s exciting to finally see more people trying it.

The idea is simple: AI workflows are becoming increasingly multi-agent, but they’re also becoming harder to observe, secure, and optimize. Gate sits between your agents and the models they use, giving you a single place to route requests, monitor activity, and apply security and optimization policies.

Whether you’re using Claude Code, ChatGPT, Gemini, Qwen, or any of the 100+ models available through Gate, you can route everything through one platform instead of managing each provider separately.

Some of my favorite features are:

• Transparent routing across providers and models.

• Prompt compression and intelligent caching that typically reduce token usage by 20–40%.

• Built-in prompt injection detection and sensitive data protection.

• A unified view of what your AI agents are actually doing.

We’re building Gate because we believe AI infrastructure should be secure, observable, and efficient—not just another API gateway.

If you’re experimenting with AI agents or production AI systems, I’d love to hear your thoughts and feedback!

Hey everybody! I'm Alex from Constellation.

Gate AI is our answer for multi-agent AI users and teams. All of your messages and sessions flow through a single platform so that you have a view into what your agents are doing, even when you're not watching directly. You can keep your existing subscriptions to Claude Code, ChatGPT, or any other and route your requests through Gate. Or, you can connect directly to any of the 100+ models that we serve directly - mix and match.

Gate does inline prompt compression and caching for your requests which allows you to save tokens without changing model outputs. Most users see 20-40% token savings just by routing through the platform. We scan every message for prompt injection attacks and personal data leaks, allowing you to block, flag, or redact the request based on your settings.

Check out the platform and let us know what you think! Happy to answer any questions you might have.

Quick disclaimer: I’m part of the Constellation Gate team, so I’m not exactly neutral here. But I’m also using it on my own projects, so this is from real usage.

I’m running https://openpoker.ai/ and https://theupsiderai.com/.

For The Upsider AI, this matters a lot because the product uses AI workflows that deal with prompts from posts of users on X. That means prompt injection is a real concern.

Having Constellation Gate in front gives me more confidence that the workflows are protected, sensitive data has another layer of defense, and everything is logged with a proper audit trail.

The part that surprised me most was the token savings. On The Upsider AI, I’m seeing around 50% token savings so far. That is huge for me.

So yes, I’m biased because I’m part of the team. But I’m also using this as a builder, and it already feels like one of those tools I don’t want to remove from my stack.

Protection, visibility, and savings in one place.

Hi @product . Dave here, CPO at Constellation Network. @Gate AI is what we've been building since March.

Prompt injection is OWASP's #1 LLM threat. The commercial defenses I could recommend to a friend a year ago all started at six figures. If you're one dev running a coding agent, the honest answer has been "figure it out yourself." That's the gap we built Gate AI to close.

Point your AI agent at Gate. No code changes. Inherit prompt-injection defense (F1 97.4% at 1% FPR across 16 public benchmarks; full methodology on arXiv at 2606.02959, we published it so the numbers can be audited), secret and PII scanning, and an audit trail sealed to Constellation's Digital Evidence layer that a regulator can verify without trusting us. Compression saves 20%+ tokens automatically. Early access pro users are running closer to 30%+.

Free tier available, no card. Paid and pay-as-you-go for teams and heavier usage.

What I most want feedback on: does the zero-code onboarding hold for your setup? Does the audit trail cover what your compliance team asks for? If something is confusing, tell me. We'll fix it fast.