Aikido alternative for AI-built apps — deeper specialization, zero billing during beta
Aikido is the SMB-friendly DevSecOps consolidator at $250/mo. Securie targets the same vibe-coder audience with deeper AI-built-app specialization and no billing during early access.
Aikido Security is the DevSecOps consolidator aimed squarely at the SMB and startup market that found Snyk too expensive and too noisy. The pitch is appealing: one dashboard for SAST + SCA + cloud posture + IaC + container scanning + secrets, priced at $250/month base for up to 10 users, with straightforward scaling from there. For a Series-A company trying to pass their first SOC 2 audit without hiring a dedicated AppSec engineer, Aikido is a reasonable turn-on-and-forget choice.
The honest tradeoff with consolidators is depth. Aikido covers every category adequately, but rarely the best-in-class. For teams whose risk model is dominated by generic application security hygiene — no framework-specific weirdness, no AI features, no Supabase-style novel access models — the adequate coverage is sufficient. For teams building AI-generated applications on Next.js + Supabase + Vercel, the same consolidator shape becomes a weakness: the specialists who would catch the Supabase RLS misconfiguration or the prompt-injection vulnerability are either missing entirely or implemented at community-plugin depth rather than first-class.
This page compares Aikido and Securie for that specific slice. If you run a heterogenous application portfolio where breadth matters more than specialist depth, Aikido's consolidator model is reasonable. If you run a focused AI-built application where the novel bug classes live outside traditional SAST coverage, Securie's specialist depth is the material difference.
Why people leave Aikido
- $250/mo (+$70/extra user) adds up for small teams
- Consolidator approach = shallow per-category
- No AI-feature specialists (prompt injection, tool abuse, RAG poisoning)
Where Aikido actually breaks down
Consolidator breadth comes with specialist-depth cost
Example: Aikido's SAST is built on open-source scanners (Semgrep, gitleaks, Trivy) with a unified UI on top. The UI is competent, but the detection quality inherits from the underlying scanners — including their well-known limitations. The Supabase RLS coverage is at best what the community Semgrep rules provide; the AI-feature coverage (prompt injection, tool-scope abuse) has no dedicated detector because the underlying scanners do not have one.
Impact: Teams adopt Aikido expecting a modern, AI-aware security tool and find that the AI-specific bugs they worry about are not detectable at all. The 'dashboard with everything' marketing creates an expectation the underlying engines do not deliver. Incident post-mortems then reveal gaps that were never covered.
Pricing scales faster than it looks
Example: Aikido's $250/month base covers up to 10 users. Each additional user is $70/month. A 15-person team is $250 + 5 × $70 = $600/month = $7,200/year. A 25-person team is $250 + 15 × $70 = $1,300/month = $15,600/year. At that size, the 'affordable consolidator' framing starts to feel less distinguishable from the incumbent tools it was supposed to undercut.
Impact: Teams budget at the base price and discover at hiring growth that the per-user ramp is significant. Renewal discussions then focus on seat-counting rather than on what the tool is actually detecting, which is the wrong conversation.
No sandbox verification — same false-positive problem as upstream scanners
Example: Aikido inherits the pattern-matching approach of its open-source foundations. A finding from Aikido's SAST is a Semgrep pattern match; a finding from Aikido's SCA is a manifest lookup; neither verifies exploitability. The dashboard layer does not add runtime proof. For AI-generated code where pattern matches are unreliable, the result is the same triage-tax as standalone Semgrep, just with a prettier UI on top.
Impact: The value proposition of 'one dashboard for everything' assumes the quality of findings is adequate for each category. When the underlying detection is pattern-based and the application is AI-built, the consolidator offers no improvement over the underlying tools at lower cost (open-source Semgrep + Trivy + gitleaks is free and gives equivalent detection quality).
Auto-fix is limited to a subset of simple cases
Example: Aikido's auto-fix suggestions cover dependency upgrades (bump the vulnerable package version) and some simple SAST suggestions (escape a string, add a null check). Framework-specific fixes — the Supabase RLS policy needs USING (auth.uid() = owner_id), the Next.js middleware needs an explicit matcher, the Server Action's Zod schema needs .strict() — are not auto-fixable because the tool does not model the framework semantics.
Impact: The auto-fix feature in marketing suggests broader coverage than the product delivers. For AI-generated apps where most bugs are framework-specific rather than generic pattern-matches, the auto-fix feature is usable for maybe 15-25% of findings; the rest require manual fix authoring.
Cloud posture is light-touch; not a replacement for Wiz or Orca
Example: Aikido's cloud posture coverage is basic — inventory of AWS/GCP/Azure resources, some misconfiguration checks, dashboard visualization. It is not a replacement for dedicated CNAPPs (Wiz, Orca, Lacework) at enterprise scale. For small teams with simple cloud footprints, the light-touch is sufficient; for teams approaching mid-market with complex multi-cloud deployments, the depth gap shows quickly.
Impact: Teams outgrow Aikido's cloud posture coverage around the 30-50 person mark and then face a decision: upgrade to a dedicated CNAPP alongside Aikido, or migrate both cloud and application scanning to a different consolidator. Either path disrupts the 'one tool for everything' value proposition.
Why Securie instead
Deeper on AI-built apps
Aikido covers everything shallowly; Securie specializes on the Next.js + Supabase + Vercel + AI-feature surface where vibe-coded apps actually ship.
Sandbox verification
Aikido's pattern-matching produces the same false-positive tax as Snyk/Semgrep. Securie's sandbox eliminates it.
$0 during early access
Aikido is $250/mo from day one. Securie is $0 now, founding-rate forever.
Feature matrix — Aikido vs Securie
| Area | Aikido | Securie |
|---|---|---|
| Scope philosophy | Consolidator — SAST + SCA + cloud + IaC + container + secrets | Specialist fleet — dedicated agent per AI-built-app bug class |
| SAST engine | Open-source (Semgrep, gitleaks) under Aikido UI | Custom specialist agents; sandbox-verified |
| Finding verification | Pattern match from underlying scanners; no sandbox | Firecracker-sandboxed exploit reproduction per finding |
| Supabase RLS | Community Semgrep rules; partial | First-class specialist parsing CREATE POLICY |
| AI-feature security | Not covered | Prompt injection, tool-scope abuse, RAG poisoning specialists |
| Auto-fix coverage | Dependency bumps + simple pattern replacements | Framework-aware patch, sandbox-verified per finding |
| SCA | Manifest-based; broad coverage via curated DB | Launch: malicious-npm + 15-min CVE-to-block; full SCA on roadmap |
| Cloud posture | Light-touch inventory + misconfig | Cloud-adapters roadmap (S3 + IAM + secret-leak) at Series A |
| Container scanning | Trivy under the hood | Not at launch |
| IaC scanning | Via Checkov integration | Terraform + K8s specialists at launch |
| Secret scanning | gitleaks patterns | Live-validated + auto-rotate PR |
| Deploy-gate | CI/CD integration only; no hosting-layer block | Vercel Integration blocks at hosting layer |
| Attestation | Findings export; audit log | Signed in-toto + SLSA per scan |
| Pricing (15-user team) | $7,200/yr base + add-ons | Free during early access; founding-rate for life |
The deeper tradeoff
The consolidator thesis has a real market fit: security buyers at small and mid-sized companies want one vendor contract, one dashboard, one integration to maintain, and one number to explain to procurement. Aikido has executed on this thesis well — the UI is clean, the onboarding is fast, the pricing is transparent, and the category coverage is genuinely broad. For a Series-A company that needs to tick 'has a vulnerability-management program' on a SOC 2 audit and wants the program to be real rather than theater, Aikido is a reasonable starting point.
The architectural decision underlying Aikido's product is to compose open-source scanners behind a unified experience. Semgrep for SAST, Trivy for containers, gitleaks for secrets, Checkov for IaC. This composition is a clever way to ship breadth quickly, and it works for a large class of customers — the customers whose risk model is dominated by generic application security hygiene where the open-source engines are adequate. The dashboard layer adds triage workflow and a single bill rather than improving detection quality.
For teams whose risk model is dominated by AI-generated code on AI-native frameworks (Next.js 15 App Router, Supabase, Vercel AI SDK, langchain-style LLM tool calling), the open-source engines are not adequate because the bugs do not match their patterns. Aikido's dashboard layer cannot add detection it does not have underneath. The gap is not a UX gap or a pricing gap; it is an architectural gap between 'aggregate pattern engines' and 'specialist exploit engines'.
Securie's approach is the inverse: rather than compose existing pattern scanners, build a specialist fleet where each agent owns one class of bug on a specific framework (Supabase RLS specialist, Next.js BOLA specialist, prompt-injection specialist, etc.), and require every finding to pass through a Firecracker sandbox that reproduces the exploit. The fleet is narrower than Aikido's consolidation at launch — no container scanning, limited cloud posture — but the depth per-specialist is materially different on the AI-built-app surface.
The right call between Aikido and Securie depends on the shape of your application portfolio. A team maintaining ten unrelated repos across three languages with simple security needs is well-served by Aikido's breadth. A team focused on one AI-built application where the risk model is dominated by Supabase RLS, broken access control, and AI-feature abuse is better served by Securie's specialist depth. The tools are not directly substitutable; they are designed for different shapes of risk.
Pricing
Aikido: $250/mo base + $70/extra user. Securie: $0 early access, lifetime founding-rate afterward.
Migration path
- Sign up for Securie during early access (free)
- Install alongside Aikido for 2 weeks
- Compare findings on your specific stack
- Cancel Aikido if Securie's coverage is sufficient for your stack
Extended migration playbook
Step 1: Scope your coverage requirements honestly
What: List the security categories your SOC 2 / board / compliance needs you to cover: SAST, SCA, secret scanning, IaC scanning, container scanning, cloud posture, deploy-gate, audit artefact. Mark which are truly required for your current stage and which are forward-looking.
Why: Aikido's strength is breadth; Securie's strength is depth on a focused subset. The comparison is meaningful only when scoped to the categories you actually need today. A team that will not touch a container for 18 months should not buy tooling priced on container-scanning coverage.
Gotchas: Beware of SOC 2 boilerplate lists. Many SOC 2 control descriptions name categories (container scanning, IaC scanning) that the auditor will accept as 'not applicable' if you do not actually run containers or write Terraform. Right-size the scope before picking a tool.
Step 2: Run Securie on your primary AI-built app alongside Aikido
What: If Aikido is already installed, add Securie on the same repositories. Let both tools scan every PR for two weeks. Track findings by category: which tool catches Supabase RLS issues, which catches dependency CVEs, which catches cloud misconfigurations.
Why: The per-category catch rate is the comparison that matters. Aikido will catch more dependency CVEs (broader SCA); Securie will catch more Supabase / AI-feature bugs (specialist depth). The real question is which categories drive your actual incidents.
Gotchas: Aikido's findings can be noisy on Next.js App Router code — the default Semgrep rules have known false-positive patterns on Server Actions. Do not conflate 'many findings' with 'better coverage' during the comparison.
Step 3: Map detection to incident history
What: Walk your last 12 months of security incidents, near-misses, or pentest findings. For each, mark: which tool would have caught it? If Aikido and Securie both would have caught it, note the category. If only one would have, that is a concrete data point.
Why: Incidents are the ground truth. Marketing-level comparisons are noise; what actually went wrong in production is signal. Most teams find that their incident pattern concentrates in 2-3 categories, and those categories determine the right tool.
Gotchas: No incident history? Run a third-party penetration test (even a cheap one, $5-10K) to establish the ground truth. Pentest findings are the closest proxy to 'real bugs we do not know about'.
Step 4: Decide: consolidate on one, or run both with clear boundaries
What: If 80%+ of your incidents map to Securie's specialists, consolidate on Securie and keep Aikido only for categories Securie does not yet cover (containers, cloud posture breadth). If incidents span widely, Aikido's consolidator model fits your risk shape and Securie is optional rather than required.
Why: Paying for two overlapping tools is expensive and distracting. Clear category boundaries — 'Aikido owns X, Y, Z; Securie owns A, B, C' — make the dual-tool model sustainable. Overlapping scope with unclear ownership is where both tools become shelf-ware.
Gotchas: Dashboards proliferate. Pick one as the source-of-truth for SOC 2 evidence and keep the other as reference. Dual-source-of-truth is an audit pain point.
Pick Securie if…
You're on a vibe-coding + AI-native stack and want specialist depth.
Stay with Aikido if…
You need broad polyglot coverage across many unrelated codebases.
Common questions during evaluation
Is Aikido a better fit for small teams than Securie?
For small teams with broad-but-shallow needs (one ten-person team maintaining a few unrelated repos, simple cloud, no AI features), Aikido's consolidator model can be more practical. For small teams focused on one AI-built application where the risk concentrates in framework-specific bugs, Securie's specialist depth is more useful and the pricing difference (free during early access vs $250/mo base) is significant.
Does Aikido cover Supabase RLS?
Aikido's Supabase coverage is at community-plugin depth via its underlying Semgrep engine. It catches obvious misconfigurations (USING (true) policies) but the more common AI-generated bugs — auth.role() instead of auth.uid() in the policy, WITH CHECK clauses missing on INSERT policies — typically slip through. Securie has a dedicated Supabase RLS specialist that parses CREATE POLICY statements and models the auth chain.
Can I consolidate container scanning on Aikido and app scanning on Securie?
Yes, and this is a reasonable split for teams where Securie's launch scope (no container scanning) is a gap. Aikido's container coverage is Trivy-based, which is a mature OSS scanner. Run Aikido for container + cloud posture + IaC, Securie for the application-layer specialists and sandbox verification. Clarity on category boundaries avoids double-paying for overlapping SAST.
How does Aikido's pricing compare to Securie long-term?
Aikido's pricing is $250/month base (10 users) + $70/user/month above that. Securie is free during early access and customers who sign up during this window receive a founding-rate discount for life when paid tiers ship. Precise long-term pricing for Securie is Series A+ and will be published before the founding-rate window closes; the intent is to remain competitive with Aikido's per-user structure for equivalent team sizes.
Does Aikido's cloud posture replace Wiz for us?
For small cloud footprints (single AWS account, dozen-ish resources, no Kubernetes), Aikido's light-touch cloud posture can cover the basics. For mid-market and enterprise cloud complexity (multi-account, multi-cloud, Kubernetes, serverless), it is not a Wiz / Orca / Lacework replacement. Teams typically outgrow Aikido's cloud posture at the 30-50 person mark.
Is the UI difference material between Aikido and Securie?
Aikido's UI is competent and optimised for dashboard-driven triage — a queue of findings with filters, assignment, and status. Securie's UI is optimised around the sandbox artefact per finding — the exploit trace, the proposed patch, merge-or-dismiss. The UX difference reflects the underlying data model: a pattern-match queue vs an exploit-proof ledger.
Can Securie's specialists be turned off per-repo?
Yes. The specialist fleet is individually configurable per repository — you can disable the Supabase RLS specialist on a repo that does not use Supabase, or disable the prompt-injection specialist on a repo with no LLM features. Disabling specialists does not change pricing; the fleet is included, you just reduce irrelevant noise.
What about Aikido's AI SPM (AI Security Posture Management) feature?
Aikido launched AI SPM in late 2025 as an inventory-and-risk-scoring view of AI usage across a codebase. It is an AI visibility layer, not an AI-bug detector — it tells you what AI libraries your code imports, not whether your prompt-injection-handling is correct. Securie's AI-feature specialists address detection; Aikido's AI SPM addresses inventory. These are complementary rather than overlapping.
Verdict
Aikido is a genuine answer to 'the incumbent is too expensive and too noisy for our stage', and for teams whose risk model distributes across many categories (SAST + SCA + cloud + container + IaC) without concentrating in any specific one, the consolidator model fits. For a Series-A startup passing its first SOC 2 without a dedicated security hire, Aikido is a reasonable starting point.
For teams whose risk concentrates in the AI-built-app surface — Supabase RLS, Next.js access control, AI-feature safety, leaked inference keys — the consolidator's breadth is the wrong shape. Depth per-specialist is what catches those bugs, and depth is the opposite of what a composed-open-source dashboard can provide. Securie's fleet is narrower but materially deeper on that surface; for this profile the consolidation gain is a coverage loss.
The practical path is to run both for two weeks on your actual repository, map findings to your incident history, and let the data decide. If your risk is truly broad and shallow, Aikido remains the right answer. If your risk is narrow and deep on AI-native patterns, Securie is.