Ciris vs Tough Tongue AI for Sales

Ciris and Tough Tongue AI for Sales 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.

Tough Tongue AI for Sales

Tough Tongue AI is an agentic platform from Tough Tongue AI that lets builders deploy multimodal voice agents — ones that can share slides, draw on whiteboards, and analyze facial expressions alongside speech — without standing up the infrastructure from scratch. The vendor states you can embed a production-ready agent with four lines of code, which means teams skip the build-and-maintain cycle that raw voice API platforms require. The analysis layer processes audio directly rather than relying on transcripts, so hesitation and tone survive into the coaching output. The platform does not offer self-hosting, so any team with a hard data-residency requirement hits a wall before the first pilot. White-labeling and API access are available, but API depth for custom integrations needs verification against the docs before you architect around it.

Attribute	Ciris	Tough Tongue AI for Sales
Pricing	Free	Paid
Price	—	$12/month
Free trial	No	No
Open source	Yes	No
Has API	No	Yes
Self-hosted option	Yes	No
Platforms	iPhone, Android, desktop, pip	Web, phone, Google Meet, Zoom
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.	Multimodal analysis processes voice tone, hesitation, and facial expressions directly — not just transcripts — so coaching output for sales reps and interview candidates reflects how they said it, not just what they said. White-label embedding described as four lines of code, which means teams building on top of the platform skip a custom UI build and ship to end users without the platform's branding showing through. Pre-built scenario library covers sales, negotiation, leadership, and interview prep out of the box, so trainers and coaches can run a pilot without authoring from scratch. Agentic architecture with real tool access — whiteboards, slides, code editors, image generation — means agents can conduct structured sessions that go beyond back-and-forth conversation, which static voice bots cannot replicate. CRM-triggered outbound calling and inbound booking agents are described as production-ready use cases, so sales and customer service teams can deploy beyond training into live customer interactions.
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.	No self-hosted deployment option exists — the platform is cloud-only, so any team operating under data-residency mandates or air-gapped security requirements cannot run a compliant pilot, and they will evaluate on-premise-capable alternatives instead. The platform's API depth for custom integrations is not fully enumerated in the scraped content; teams planning to build deep CRM or LMS integrations will hit undocumented limits and need to work through the docs and support before committing their architecture. Adaptive scenario behavior relies on the platform's own agent logic, which means scenario authors who need deterministic branching or compliance-scripted conversation flows may find the agentic model too unpredictable for regulated training contexts — at which point teams revert to static scripted tools or build a custom layer on top.

Bottom line

Ciris is free while Tough Tongue AI for Sales is paid; Ciris is open source; only Tough Tongue AI for Sales exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Ciris and Tough Tongue AI for Sales?

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

Is Ciris better than Tough Tongue AI for Sales?

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.