OpenLegion vs Zamp

OpenLegion and Zamp are both ai agent apps tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

OpenLegion

Each agent gets its own isolated container, spend cap, and vault-proxied credentials — so a rogue agent can't drain your API budget or leak credentials to the next task in the queue. The platform deploys a coordinated fleet from a plain-English description of the function you need: a sales pipeline, a content studio, a research desk. Credential handling and per-agent budgets are locked down by default, which means you're not retrofitting security after something goes wrong. The ceiling appears when your workflow needs branching logic that the template model can't express — at that point you're describing edge cases in natural language and hoping the agent interprets them correctly. Teams with deterministic multi-step requirements often add a separate orchestration layer to compensate.

Zamp

The vendor describes a four-day onboarding arc — connect your existing tools, walk through your process, correct the agent's early runs, then hand off volume. Testimonials from Mindbody's finance team confirm invoice processing runs end-to-end with human review only when Zamp surfaces a question. It monitors and executes without waiting for a prompt, which separates it from chatbot-style tools. The ceiling appears where process logic is genuinely novel or where your team's judgment call changes week to week — Zamp learns from correction, but that feedback loop takes cycles to stabilize. Pricing is opaque until you book a demo, and there is no self-hosted deployment path.

Attribute	OpenLegion	Zamp
Pricing	Paid	Paid
Price	$19/mo	—
Free trial	7 days	No
Open source	No	No
Has API	Yes	No
Self-hosted option	Yes	No
Platforms	Web, Self-hosted (Docker)	Web/SaaS (app.zamp.ai)
Released	2026-02	—
Pros	Per-agent spend caps enforce budget ceilings at the container level, so a misconfigured agent or a prompt injection that triggers excessive tool calls cannot consume your entire LLM budget before you notice. Vault-proxied credential handling means raw API keys and account credentials are never passed between agents in plaintext, which removes a common attack surface in multi-agent setups where credentials flow through shared memory. Support for over 100 LLM providers with no markup on usage, so switching the model backing a specific agent — say, moving a high-volume scraping agent from a premium model to a cheaper one — is a configuration change, not a rebuild. Container isolation per agent means a failure or security event in one agent's environment does not propagate to the rest of the fleet, so a single broken workflow doesn't take down concurrent production tasks. Native trigger integrations with Slack, Discord, Telegram, WhatsApp, and webhooks mean agents can be kicked off from tools your team already uses, so you avoid building a separate scheduling or event layer to connect the platform to your existing stack.	Connects to existing tools — ERPs, inboxes, spreadsheets — without an IT integration project, so your team does not lose months before the agent is running on real work. Runs processes end-to-end without a prompt each cycle, so your team is not the bottleneck managing a tool that should be managing itself. Learns from each correction and applies that learning across all future similar tasks, which means the error rate compounds downward instead of requiring someone to manually update a rule tree every time a new exception appears. Escalates to humans when it hits a genuine decision point rather than silently failing or dropping work, so the output your team sees has already been filtered for the cases the agent cannot resolve. Covers a wide range of operational roles — finance, compliance, HR, customer success — so a single deployment can absorb repetitive work across departments rather than requiring a separate tool per function.
Cons	Workflows that depend on precise conditional branching — route this lead differently based on company size, or skip invoice processing if the vendor field is blank — have to be described in natural language rather than defined in code. At production volume, the agent's interpretation drifts, and teams running exception-heavy operations report adding a rules layer outside the platform to catch the cases that fall through. There is no free tier. Evaluation requires a paid commitment with a money-back window. Teams that need to run a live proof-of-concept against their actual data before budgeting the tool will find the evaluation model friction — and some will default to an open-source alternative like n8n or a code-first framework they can run locally at zero cost. The platform is closed-source, which means teams with strict compliance requirements who need to audit the agent runtime itself — not just the action logs — cannot inspect the execution layer. Organizations in regulated industries that hit this wall during security review switch to a self-hostable, open-source orchestration framework where the full stack is auditable.	Processes that change frequently — seasonal policy updates, evolving compliance rules, shifting approval hierarchies — require ongoing correction cycles that never fully stabilize; teams in those environments report a sustained supervisory burden rather than true hands-off automation. There is no self-hosted or on-premise deployment option. For financial institutions or healthcare operations with hard data residency requirements, this is not a configuration gap — it is a disqualifier. Teams in those environments move to vendors with private cloud or on-prem options rather than working around it. The feedback-learning model means the agent's accuracy in the first weeks depends entirely on the quality and volume of corrections your team provides; teams that under-invest in the day-three review phase report slower accuracy gains and extend the period where human oversight is heavy rather than light.

Bottom line

Only OpenLegion exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between OpenLegion and Zamp?

OpenLegion is Paid, while Zamp is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is OpenLegion better than Zamp?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.