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Ciris vs PUNKU.AI

Ciris and PUNKU.AI 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

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.

PUNKU.AI

PUNKU.AI

PUNKU.AI targets teams that want a deployed agent without an engineering sprint behind it. The vendor states agents can be created in minutes using natural-language instructions, with integrations like bookingkit cited as production references across 200+ businesses. The platform covers sales, marketing, support, research, and operations use cases — ticket selling, outbound calling, and quote generation are shown as live examples. Where this hits a wall is customization depth: teams that need complex branching logic or bespoke API behavior beyond the supported integrations have no self-hosted escape hatch and no open-source layer to extend. At that point, the choice is waiting on the vendor roadmap or rebuilding in a more programmable environment.

AttributeCirisPUNKU.AI
PricingFreePaid
Price€39/mo
Free trialNo14 days
Open sourceYesNo
Has APINoNo
Self-hosted optionYesNo
PlatformsiPhone, Android, desktop, pip
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-English agent creation means non-technical teams can define, deploy, and adjust agents without writing or reviewing code — so the bottleneck shifts away from engineering for routine automation tasks.
  • ISO 27001 certification and GDPR compliance are vendor-stated, which means procurement review for European or regulated-industry deployments does not start from zero.
  • Self-improving agent behavior is described as built into the platform, so prompt drift and performance degradation do not require a dedicated person monitoring and manually retuning agents.
  • Freemium entry point means a team can validate whether an agent handles their actual workflow before committing budget — avoiding the sunk cost of a paid contract on an unproven use case.
  • Named business integrations (bookingkit cited as a live reference) signal production-tested connectors rather than theoretical compatibility, which reduces the risk of discovering an integration is broken only after you have built around it.
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.
  • Custom branching logic — agents that need to route differently based on what the previous step returned — has no visible code escape hatch. Teams that hit this wall on their second or third agent have no extension layer to reach for; the only path forward is switching to a platform that exposes agent logic programmatically.
  • No self-hosted option means your data and agent runtime live on PUNKU.AI's infrastructure. Organizations with strict data residency requirements or internal security policies that prohibit third-party cloud execution cannot satisfy those requirements with this tool and must evaluate self-hostable alternatives.
  • The integration catalog appears limited to what the vendor has built and maintains. If your critical business tool is not on that list, there is no documented mechanism to connect it yourself — teams in this position report building a parallel workaround or abandoning the platform entirely for one with open API connectivity.
Bottom line

Ciris is free while PUNKU.AI is paid; Ciris is open source. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Ciris and PUNKU.AI?

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

Is Ciris better than PUNKU.AI?

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.

Ciris vs PUNKU.AI: which should I pick?

Pick Ciris if its pricing model, openness, or platform fit matches your constraints; pick PUNKU.AI otherwise. Check free-trial availability on each listing if you want to test before committing.

Comparison data is sourced and verified by the AIDiveForge data pipeline. AIDiveForge is editorially independent.