Train your AI assistant on everything your team knows
Centralize documentation, teach the bot how support and sales really work, and fine-tune AI models on your data — so every reply feels like it comes from your best product expert.
Works for support, sales and technical teams • No ML background required
Organize all your knowledge into clean, AI-ready knowledge bases
Start with a simple, lightweight knowledge base, then grow into multiple spaces for support, sales and technical teams — up to unlimited knowledge bases across brands and regions.
Flexible structure
Group content by topics, products, features or use cases. Reorganize without breaking the AI — it automatically adapts to your new structure.
Multiple content sources
Import articles from your help center, internal docs, PDFs or other tools and keep them in a single, AI-readable space.
Growth-ready limits
Begin with a small knowledge base to validate the bot, then scale up to many bases — one per brand, product or region — as automation becomes critical.
Knowledge bases are where your bot "lives and learns". You can start with a single lightweight base of 20 documents to test the concept, then expand to multiple spaces as your product and team grow — for example, separate knowledge bases for customer support, self-serve onboarding, internal operations and technical documentation.
Each knowledge base can contain hundreds or even thousands of articles, FAQs and guides. The platform automatically ingests content, cleans it, and structures it so AI can navigate, cross-reference and synthesize information, instead of just quoting a random paragraph.
For enterprise setups, knowledge bases can be organized by brand, region or department, so that each market or product line can have its own version of policies, pricing and legal texts — while the AI still sees the full picture and routes users to the right space.
Outcome: your AI never "guesses" from scattered files; it relies on well-structured, always-current knowledge.
From basic FAQ lookup to powerful semantic search across all docs
Let users (and your team) find answers in seconds — whether you have a short FAQ, a growing help center or enterprise-grade documentation across multiple systems.
Basic FAQ & help center search
Quickly set up AI search for small FAQ sets and help pages — the bot recognizes synonyms, typos and natural language questions.
Multi-source semantic retrieval
Pulls the right pieces from multiple documents and stitches them into a single, clear answer with optional detail and links.
Scales with your documentation
Whether you have 20 articles or thousands of pages, search quality and speed remain stable as your knowledge base grows.
Enterprise-grade relevance
Advanced plans use powerful semantic models tuned on your domain to understand nuance, policies and edge cases with much higher precision.
At the simplest level, AI search replaces rigid keyword lookups with intelligent matching: the bot understands the meaning of the question and finds the most relevant pieces of content, even if the wording is completely different from your article titles.
As your library grows, AI search scales with it. The engine indexes FAQs, knowledge base articles and long-form documentation, then uses semantic search to retrieve the right paragraph or step-by-step guide. It can combine excerpts from several sources, explain the result in plain language and link back to the original docs for power users.
For enterprise plans, AI search can extend beyond docs: into data sources, internal tools and knowledge bases segmented by brand or region. That lets your bot answer questions like "What are our refund rules for Germany?" or "How do I migrate from Plan A to Plan B?" using up-to-date, compliant information.
Outcome: users get accurate answers faster, and your team spends less time searching through old docs.
Separate knowledge for support, sales and technical teams
Keep different knowledge worlds clean — support macros, sales playbooks, developer docs — while your AI understands how they connect and when to use each one.
Per-team knowledge spaces
Create distinct segments for support, sales, marketing, product, engineering or partners and assign content accordingly.
Brand & region specific content
Keep localized policies, pricing and legal texts separate but connected, so AI always picks the right variant for that user.
Channel & audience targeting
Use different content sets for web, in-app chat, partner portals or internal help, while reusing the same AI engine underneath.
Policy & compliance guardrails
Mark sensitive or internal-only content and decide when it can be used, or when the bot must escalate to a human instead.
In growing teams, support, sales and engineering don't speak the same language — and that's okay. Content segmentation lets you define separate knowledge spaces for each function, so the bot can answer like a CSM in one conversation and like a solutions engineer in another.
You can assign content segments to channels, pages, intents, user types or brands. For example, a pricing page might combine sales scripts with policy snippets, while the developer portal uses only technical docs and API references.
The AI respects these boundaries: it won't quote internal-only notes in public, mix outdated edge-case workarounds into general advice, or use overly technical language with non-technical users — unless you explicitly want it to.
Outcome: each audience gets answers that match their context, without exposing the wrong information.
Tune AI models on your tone, policies and workflows
Go beyond generic chatbots. Train dedicated AI models on your content and conversations, so the assistant speaks like your brand and respects how your operations really work.
Basic tuning on your data
Quickly adapt the model to your terminology, product names, typical requests and preferred tone of voice using existing content.
Training on conversations
Use historical tickets and chats as training material. Show the AI which responses are "good" and which should be avoided or escalated.
Workflow-aware behavior
Teach the model your real workflows: verification steps, approval rules, required fields and escalation paths for specific scenarios.
Dedicated enterprise models
For large teams, train specialized models aligned with your policies, compliance needs and multi-brand structure — with dedicated support.
Basic tuning layers your documentation and example conversations on top of a strong base model. That's enough to align terminology, tone of voice and the most common support flows with minimal setup.
As your usage grows, you can move to deeper training: feeding the model with curated Q&A pairs, real-world tickets, escalation rules and playbooks for complex situations. The model learns which answers are acceptable, which phrases to avoid, and what to do when it's not confident.
At the highest level, you can train dedicated models per brand, region or product line. Each of them can be optimized for specific regulations, SLAs, pricing rules and internal processes — while still being managed from a single console.
Outcome: the bot feels less like a generic assistant and more like a seasoned team member who "gets" your business.
Together, Knowledge & Training turn AI into a real part of your team.
Start with a small knowledge base, add semantic search and content segmentation, and grow into fully tuned models that know your product better than any FAQ ever could.