Ciris vs Triggered Agents by Adaptive

Ciris and Triggered Agents by Adaptive 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.

Ciris

CIRIS runs a signed reasoning agent on your phone or a home device, with no warehouse in the middle for the closest privacy circles. The vendor describes two paths: fully on-device using a small model like Gemma 4, or free hosted inference for phones that can't run a local model — both paths produce cryptographically signed outputs. Every claim the agent makes carries an ed25519+post-quantum signature, so you can audit it, revoke trust, and re-open any conclusion built on a bad source. The architecture depends on a 'social circle' data model; data in your innermost circles never sends the network message that would let anyone request it. Teams needing broad third-party integrations or a hosted API endpoint will find neither here.

Triggered Agents by Adaptive

Adaptive lets you describe work in plain language — 'flag suspicious signup domains every morning' or 'draft weekly product updates from GitHub' — and deploys agents that loop through the steps, call connected tools, and surface results without waiting for you to click through each stage. Agents can run in parallel, so a sales pipeline workflow and a development update feed operate independently at the same time. The approval controls let you stay in the loop on sensitive steps without babysitting routine ones. Where it strains: teams with complex conditional branching across departments, or those who need fine-grained workflow versioning, will hit the ceiling of a conversational-first build surface faster than teams doing linear recurring tasks.

Attribute	Ciris	Triggered Agents by Adaptive
Pricing	Free	Paid
Price	—	$20/month
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	iPhone, Android, desktop, pip	Web-based with native iOS app
Released	—	2025-04
Pros	On-device inference with no data center in the path for supported hardware, which means your input and the agent's reasoning never leave the device — no logs elsewhere, no third-party retention. Cryptographic signing on every agent output using ed25519 plus a post-quantum scheme, so you can trace exactly what the agent claimed, who agreed, who pushed back, and revoke trust retroactively if a source is found to be misleading. Seven-circle privacy model where innermost circles are structurally isolated — not by policy enforcement but by the absence of the outbound network message — which means there is no configuration mistake that can accidentally expose 'self' or 'family' data. Fully open-source under AGPL-3.0 with self-hosted option, so the vendor going dark does not kill your deployment and you can audit the signing and isolation logic yourself. Hosted inference path available at no cost for low-resource devices in 29 languages, which means teams can deploy to users whose hardware cannot run a local model without building separate infrastructure.	Plain-language agent creation from existing spreadsheets or documents, so non-technical operators build functional automations without writing a line of code or waiting on a developer. Parallel multi-agent execution, which means a sales outreach workflow and a GitHub update digest run simultaneously without one blocking the other — something a single-agent queue cannot do. Step-level human approval controls, so you sign off on sensitive actions like sending emails or processing payments while the surrounding routine steps run unattended. Connections to Gmail, Stripe, Square, and GitHub out of the box, which means agents pull from and write to the tools a small business already uses rather than requiring a custom integration build. Mobile management via iOS app, so an agent running overnight outreach or morning domain flagging can be reviewed and adjusted without being tied to a desktop.
Cons	No API surface exists — there is no endpoint to call from an external pipeline, no webhook, no SDK. Any team building a product that needs to programmatically query the agent or integrate it into an existing backend hits a hard wall on day one and moves to a tool with an API. The CEWP fabric is a closed trust network; it does not bridge to standard enterprise identity systems, cloud storage, or third-party data sources. Teams expecting to connect the agent to a CRM, a document store, or an external knowledge base find no integration path and either abandon the tool or build outside the CEWP model entirely. On-device inference requires hardware capable of running a small local model. The vendor names Gemma 4 as an example. Devices that cannot meet this threshold fall back to hosted inference, reintroducing a data center into the path and partially negating the core privacy architecture for those users. The social circle and trust federation model is novel and not documented against standard compliance frameworks. Teams operating under HIPAA, SOC 2, or GDPR audit requirements cannot map CIRIS's architecture to their compliance checklists without significant interpretive work — and no audit trail export to standard formats is described.	Workflows that require branching logic — 'if the lead replied yes, route to calendar; if no, wait three days and try again; if unsubscribe, update the CRM' — hit the limits of a conversational build surface quickly. Teams with more than two or three conditional paths end up describing workarounds to the agent rather than expressing the logic directly, which makes debugging opaque. No self-hosted option exists. Teams operating under data residency regulations, enterprise security policies, or air-gapped network requirements cannot deploy Adaptive at all — at that point they move to a self-hostable alternative like n8n or a custom stack regardless of how well the agent layer fits their workflow. Paid-only features gate the full agent capability for teams on the free tier, which means prototyping a multi-agent workflow and then discovering the parallel execution or advanced integrations require an upgrade — after the build time is already spent.

Bottom line

Ciris is free while Triggered Agents by Adaptive is paid; Ciris is open source; only Triggered Agents by Adaptive exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Ciris and Triggered Agents by Adaptive?

Ciris is Free and open source, while Triggered Agents by Adaptive is Paid. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Ciris better than Triggered Agents by Adaptive?

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.