Self-Hosted vs SaaS Agent Guardrails: A 2026 Comparison

**Short answer**: self-host wins when data sovereignty, extensibility, or audit-grade evidence matter — that's most regulated verticals (healthcare, fintech, gov, defense). SaaS wins when operational simplicity and detector-update velocity matter — that's most consumer apps, internal-tool agents, and pre-revenue startups. The right decision changes over your company's lifecycle: prototype on SaaS, ship enterprise on self-host. This article walks through the tradeoffs.

## What does each model mean concretely?

**SaaS guardrails** = your agent calls a vendor's API for every safety check. Vendor hosts the detectors, the dashboards, and the audit log. Examples: Lakera Guard, Patronus, ProtectAI's hosted offering.

**Self-host guardrails** = you run the firewall daemon in your own infrastructure. Examples: AEGIS, NVIDIA NeMo Guardrails (you run it), HashiCorp Boundary patterns.

**Open-core hybrid** = self-host the engine (free, MIT), pay for the cloud control plane that gives you license-key features (multi-org dashboard, policy sync, alerting). The Tailscale / Sentry / GitLab model. AEGIS uses it.

## Where does SaaS win?

**Zero operational burden.** No Docker, no Kubernetes, no version upgrades, no infra cost. For a 5-person AI startup that hates devops, this is meaningful.

**Faster detector updates.** A SaaS vendor ships new detection patterns and your protection improves the same day. With self-host you pull a new binary.

**Centralised intelligence.** SaaS vendors see attacks across all customers; that aggregate visibility produces detection improvements faster than any single customer could generate.

**Standardised dashboard.** One UI for everyone; the vendor's design team optimises it.

For a B2C chatbot, an internal HR assistant, a low-stakes content tool — SaaS is the right call.

## Where does self-host win?

**Data sovereignty.** Your customer's data never leaves your network. For HIPAA, PCI-DSS, FedRAMP, FATF Travel Rule — this is the difference between deployable and deal-killer. SaaS guardrails require a BAA / PCI scope expansion / FedRAMP boundary inclusion — each is a multi-month negotiation.

**Air-gapped deployment.** Government, defense, and high-security industrial customers operate networks that have no outbound internet. SaaS is impossible.

**Customisation.** Add your own detector. Modify the policy DSL. Hook into your internal IdP. Forking and contributing back is encouraged in open-core.

**Audit-grade evidence.** Your auditor or regulator may need to trace exactly what happened. SaaS vendors store logs in their infra; you trust their attestation. Self-host with [cryptographic audit](/blog/cryptographic-audit-logs-merkle-sigstore) lets the auditor independently verify the data without trusting the vendor.

**Cost at scale.** SaaS pricing scales linearly with usage; self-host scales sub-linearly. At certain volumes self-host's TCO crosses below SaaS.

**Vendor lock-in escape hatch.** SaaS vendors get bought (Robust Intelligence → Cisco), pivot, or shut down. Your safety layer shouldn't be a dependency you can't replace.

For fintech, healthcare, gov, on-prem enterprise, anything compliance-heavy — self-host is the default.

## What does the hybrid (open-core) model look like?

You don't have to choose binary.

AEGIS's open-core configuration:

- **Engine (gateway daemon)** = MIT-licensed, runs on your infra. Handles every tool call. Data never leaves your network.
- **Cloud control plane** (optional) = central dashboard for your team. Multi-org policy sync, alerting, support tier features. License-key gated.
- **Update channel** (optional) = pull new detector models / policy packs from the cloud automatically.

This combines the best of both: enforcement on your hardware (data sovereignty), operational complexity drops because you're not running the dashboard infrastructure or detector R&D.

Similar to GitLab, Sentry, Tailscale, HashiCorp Vault. All four are billion-dollar companies.

## Which model should my team pick? (decision matrix)

| Concern | SaaS | Self-host | Open-core |
|---|---|---|---|
| **Operational burden** | None | High | Low |
| **Data sovereignty** | No | Yes | Yes |
| **Air-gapped capable** | No | Yes | Yes (engine only) |
| **Detector update velocity** | Highest | Lowest | Mid (cloud sync) |
| **Customisation** | None | Full | Full |
| **Audit-grade evidence** | Vendor attests | Cryptographic | Cryptographic |
| **Vendor lock-in risk** | High | None | None (engine is OSS) |
| **TCO at low volume** | Cheap | Expensive | Cheap |
| **TCO at high volume** | Expensive | Cheap | Mid |
| **Healthcare BAA** | Vendor's | Yours (clean) | Yours (clean) |
| **PCI scope** | Vendor's CDE | Yours (controlled) | Yours (controlled) |

## When does the right answer change over time?

A pattern from several design partners — the right model depends on stage:

**Stage 1 (prototype, < $0 revenue)** — pick SaaS. Speed to first iteration matters most. AEGIS Community (free + self-host) also works if you're already comfortable with Docker.

**Stage 2 (early revenue, no enterprise customers)** — SaaS still fine. Switching costs are still low.

**Stage 3 (first enterprise prospect doing security review)** — you'll hear "we can't accept SaaS for this data class." Either lose the deal or switch. ~60% of growing AI startups hit this wall around their first $1M ARR.

**Stage 4 (multiple enterprise customers, scale)** — self-host or open-core is table stakes.

Realising this *before* stage 3 saves 6 months of migration pain.

## What are the real cost numbers for self-host vs SaaS?

| Volume | SaaS (Lakera-style) | Self-host (AEGIS Community) | Open-core (AEGIS Pro) |
|---|---|---|---|
| 1k calls/day | $99-499/mo | Free + $20/mo VPS | $19/mo + $20 VPS |
| 100k calls/day | $2k-5k/mo | Free + $200/mo infra | $99/mo + $200 infra |
| 1M calls/day | $15k-50k/mo | Free + $1.5k/mo infra | $499/mo + $1.5k infra |
| 10M calls/day | Custom 6-figure | Free + $8k/mo infra | Custom + $8k infra |

At 1M+ calls/day, self-host crosses below SaaS even with full operational cost included.

## FAQ

**Can I switch between models later?**
Yes. AEGIS's open-core means you can run Community → Pro → Enterprise on a sliding scale. SaaS vendors typically have one-way doors.

**What about hybrid — SaaS for some agents, self-host for others?**
Common. SaaS for low-stakes internal agents (HR chatbot, code assistant), self-host for the agents that touch customer data.

**Does AEGIS's open-core license get more restrictive in Enterprise?**
No — the engine stays MIT forever. Enterprise adds features and support; it never removes anything from Community.

**Will SaaS vendors offer BYOC eventually?**
Some are (Lakera has hinted at it). The challenge: their detector R&D depends on aggregate data, which becomes harder if data stays in customer VPCs.

**Which model is best for federal/defense?**
Self-host, on-prem, sometimes air-gapped. SaaS is rarely accepted in classified or controlled-unclassified environments.

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**Try AEGIS open-core** → `curl -fsSL aegistraces.com/install | sh`

**Pricing** → [aegistraces.com/pricing](https://aegistraces.com/pricing)

**Discuss your deployment** → [GitHub Discussions](https://github.com/Justin0504/Aegis/discussions)