Agent

One agent. Every customer moment.

The customer-facing side of Unless — one AI Customer Agent across acquisition, retention, expansion, and support, with the Help Center it auto-generates as its public face. Browse a moment, or see the full overview.

Acquisition

Qualify, convert, educate. 24/7 on your marketing site.

Retention

See churn coming. Act before it does, inside the customer's product.

Expansion

Catch upsell signals early. Route them to the right owner.

Support

Resolve, co-pilot, learn — across every helpdesk and channel.

Engine

The platform underneath.

The back-of-house side of Unless — a Living Knowledge library that maintains itself, plus the Train → Test → Deploy → Analyze loop that keeps every Customer Agent sharper after every conversation. See how the engine compounds.

Train

Always current. Always ready. Living Knowledge + Living Context.

Test

Before a customer sees it. Preview, simulate, audit.

Deploy

One agent. The whole journey. Memory across all of it.

Analyze

Performance, value, AI maturity. All visible. All live.

Trust

Built for the EU from day one

The architecture that lets your DPO, security, and procurement teams sign off without slowing your team down. Browse the page, or jump straight to a section.

Privacy Vault

Twelve numbered measures keep sensitive identifiers home.

Compliance posture

Three pillars — sovereignty, AI Act readiness, sector readiness.

Architecture

Five EU-resident layers — touchpoints to LLM constellation.

Frameworks

EU AI Act, GDPR, DORA, OWASP — built into the platform, not bolted on.

Customers

Trusted by leaders

How regulated-Europe brands — from Visma to Onguard — turned customer success into a revenue engine with Unless.

Visma Enterprise AS

Norway's leading ERP — modernized self-service with Unless.

Helping patients

Patient self-service surged within weeks of deploying Unless.

Enhancing credit software

Financial service Onguard powers their support operations with Unless.

Ticket deflection at scale

Meet Sally, Kontek’s AI support colleague in regulated finance.

Resources

Search resources and support articles

Documentation, articles, and recipes for getting the most out of your Unless deployment — plus a help desk when you need a human.

Help center

Get-started guides and advanced playbooks for the platform.

Security and compliance

Privacy measures, security by design, and compliance guidelines.

Developer documentation

Find reference documentation for the javascript API.

The Unless cookbook

Bite-sized examples for every stage of the customer lifecycle.

Pricing

Pay per outcome. You choose.

Two equal-weight plans, both built around outcomes. Browse the page, or jump straight to a section.

The two plans

Flex (€0.99 per outcome) or Fixed (€1,999/month). Equal weight.

What's included

Full platform on both — Living Knowledge, Memory, Context.

Flex modules

Productized add-ons. À la carte on Flex, bundled into Fixed.

Frequently asked

What counts as an outcome, fair use, and switching mid-year.

Recipe

New feature and change explainer copilot

Explain product updates and regulatory changes in context so users understand what changed and what they should do next.

Updated 27 February 2026

This recipe shows how to turn release notes into in-product explanations that users can access when they need them most.

Release notes and policy updates are essential but rarely read end to end. Users encounter changes directly in the interface and want quick answers. A change explainer copilot sits next to updated features and responds to these questions.

Create an AI Skill in the Retention stage, bound to an Audience that hasn't seen the feature yet, and has the right user role to access it. The frontend can supply more information when the user is on a screen tagged as “recently changed.” The skill can then respond to open questions like “What changed here?” and “Do I need to act?” by pulling from structured release content.

Organize your inputs with flat Topics like Release-notes, Regulatory-changes, Feature-guides, and Migration-steps. Store concise descriptions and impact notes under these Topics so the AI has focused, authoritative material. This reduces the chance that it improvises reasons or invents non-existent behaviors.

For some changes, you may want to ask the user a quick clarifying question via the skill—for example, whether they want to use a specific module even if they don't have it yet. Capture these in variables like change_viewpoint to tailor explanations. The skill can then adapt the narrative without changing the underlying facts, and possibly offer an upsell.

Internally, the assistant can watch for negative sentiment or repeated confusion around a change. When many users ask similar follow-ups or appear stuck, the skill can create tasks for product and documentation owners, plus notifications with aggregated feedback. This helps you improve both the feature and its communication.

On the user side, in-app notifications are a good companion to this recipe. Use segmentation by Audiences to show small “What’s new” chips or banners that invite users to click through to the copilot. After a while, you can limit these prompts to users who have not yet acknowledged or used the new feature.

Conclusion
A new feature and change explainer copilot connects release and policy updates directly to the moments when users encounter them. With an AI Skill grounded in release- and change-related Topics, plus internal tasks and notifications for problematic updates, you reduce confusion and release-related ticket spikes.

Reach out for a personal demo

See our platform in action

Talk to our team about your use case and get a tailored walkthrough of how Unless can automate and scale your customer success workflows.