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DocsConfigure the AI Agent

Configure the AI Agent

Set the persona and tone, define clear answer rules, keep the agent grounded in the knowledge base, and control when a conversation is handed off to a human.

Where to configure this

You'll find the chatbot configuration in the dashboard under AI (console.alpheris.com → AI). There you set the persona, tone, answer rules, and handoff behavior. For the AI inbox (email and messaging) there's an additional, dedicated agent configuration under Email → AI Agent — see Inbox & AI Replies.

Alpheris answers questions in a grounded way: the agent draws its answers from your knowledge base (the crawl of your domain, shop data, uploaded files) rather than from open-ended world knowledge. For the agent to answer well, a complete knowledge base matters more than any prompt fine-tuning — see Data Sources & Knowledge Base.

Persona & Tone

The persona defines who the agent is and how it sounds. You control it via three main sliders plus a free-form system instruction.

Tone

The tone of the answers. The options are:

ToneEffectFits
FriendlyWarm, approachable, helpfulE-commerce, lifestyle
ProfessionalMatter-of-fact, polite, competentB2B, services
FormalReserved, correct and detachedFinance, legal, public sector
EmpatheticUnderstanding, reassuringHealth, sensitive topics
DirectConcise, to the pointTech, power users
CasualRelaxed, young, informalStartups, Gen Z brands

Form of Address

Controls whether the agent addresses customers formally or informally:

  • Automatic — the agent adapts the form of address to the customer's language and style (default).
  • Formal (Sie) — consistently formal address.
  • Informal (Du) — consistently personal address.

Emojis

The emoji setting controls whether the agent uses emojis: Automatic (context-dependent, sparing), On, or Off. For serious B2B presences, Off is the usual choice.

System Instruction

In the free-form system instruction, you describe the persona and fixed behavior rules in your own words. It complements the sliders above and applies to every answer.

Example instruction
You are the customer service assistant for [Company Name].
Answer in a friendly, matter-of-fact way, in short, clear sentences.
For product questions, recommend suitable items from the range.
If you can't find something in the knowledge base, honestly say
that the information is missing – never guess.
Don't promise delivery dates, discounts, or refunds.
The system instruction does not override the knowledge base. It controls style and rules — facts still come exclusively from your sources. So don't write product data into the instruction; maintain it as a data source instead.

Answer Rules

Answer Length

Choose between Short, Balanced, and Detailed. Shorter answers usually work better in web chat, more detailed ones in email support. The length can additionally differ per channel (see channel profiles further down).

Prohibited Statements

In the Prohibited Statements field, you enter things the agent must never claim or promise — such as guaranteed delivery dates, medical efficacy claims, or statements about competitors. These rules take effect in addition to the system instruction.

Clarifying Questions & Sources

  • Ask a clarifying question: If the request is ambiguous, the agent asks a targeted follow-up instead of guessing.
  • Show sources: Optionally, the agent can link the knowledge sources it used beneath the answer — useful for support-heavy sites, often distracting in sales conversations.
  • Conversation length: You can limit the maximum number of bot replies per conversation before a handoff is offered automatically.

Grounding — only from the knowledge base

Every answer is produced by hybrid, grounded retrieval: Alpheris combines full-text search and semantic vector search over your knowledge base and ranks the hits by relevance through reranking. Only the passages found this way serve as the basis for the answer.

1
Retrieval
Full-text and vector search find the most relevant passages from the crawl, shop data, and uploads.
2
Reranking
A reranker scores the hits and keeps only the most relevant passages.
3
Confidence check
If the evidence remains too thin (too few or too weak hits), the agent doesn't answer freely but falls back to the fallback.
4
Answer
The answer is formulated exclusively from the supported passages.

You can control precisely which sources feed in. In the AI configuration, the source groups can be enabled or disabled individually:

  • Website crawl of your domain
  • Knowledge base (FAQ pairs and uploaded files)
  • Shop data (products and orders, if connected)
Best practice: Create your 20 most common questions as FAQ pairs and upload your terms and conditions, shipping, and return policies as PDFs. Grounded answers are only as good as their sources — a well-maintained knowledge base prevents gaps more reliably than any prompt optimization.

Fallback Behavior

You define what happens when the agent can't find a supported answer in the fallback:

ModeBehavior
Clarifying questionThe agent asks a follow-up to narrow down the request.
HonestThe agent openly says that it lacks the information.
EscalateThe agent offers a handoff to a human.
FormThe agent shows the contact/ticket form.

Maturity: shadow → copilot → autopilot

In the AI inbox, the agent learns in stages instead of answering on its own right away. Per topic cluster (e.g. "Shipping", "Returns", "Invoicing") it goes through three phases — from silently reading along to automatic sending. This way you build trust before the agent sends messages itself.

PhaseWhat happensSending
ShadowThe agent generates suggestions in the background without the customer seeing them. You compare them with your team's actual answers.No sending
CopilotThe agent proposes ready-made answers that a team member reviews, adjusts, and approves.After approval
AutopilotFor safe clusters, the agent answers on its own as soon as confidence is above the threshold.Automatic

The move from one phase to the next doesn't happen across the board, but per cluster, and it's tied to measurable thresholds. A cluster only qualifies for promotion once enough cases exist (at least five, and no older than 14 days). For Autopilot, two hard conditions are added:

  • at least 50 accepted suggestions in the cluster, and
  • an acceptance rate of ≥ 75%.

In addition, the answer confidence must be above the cluster's threshold. The default threshold is 0.85; the more mature a cluster, the lower it may go (warm ≈ 0.78, fully mature ≈ 0.72). If confidence is below that, the suggestion stays in copilot mode for manual approval.

Complaints always stay with a human. The "Complaint" cluster is permanently excluded from autopilot — the agent generates such messages at most as a copilot suggestion, but never sends them automatically.

Channel Profiles

Tone and length adapt to the channel the message comes in through. The default profiles are:

ChannelToneLength
EmailFormalMedium
Web chatBalancedMedium
WhatsAppFriendlyShort
InstagramFriendlyShort

The global persona from the AI configuration is preserved; the channel profiles only adjust tone and answer length to suit the medium. Which channels are actually available is listed under Inbox & AI Replies.

Escalation & Handoff

You can trigger a handoff to a human in several ways:

  • On request: The customer types a keyword like "agent" or "human". You enter the triggering words as handoff keywords.
  • On low confidence: If the answer confidence is below the escalation threshold, the agent offers a handoff instead of an uncertain answer. The default value is around 0.68.
  • Via the fallback: In the Escalate or Form fallback mode, a handoff happens directly when evidence is missing.

You define the target channel for the handoff (e.g. email or ticket). Through the escalation form, you also collect contact details — optionally as a ticket, a contact request, or a lead. The form's title, subtitle, and button label are freely customizable.

Example fallback
Unfortunately I don't have confirmed information on that.
Would you like to be connected to a team member?
Our team is available Mon–Fri from 9 am to 6 pm.
Handoffs from the chat land in the Inbox, and the contacts that result go to Lead Capture. That way no conversation breaks off just because the agent can't answer a question confidently.

Test before going live

1
Check the knowledge base
Crawl complete, FAQ pairs created, important PDFs uploaded.
2
Set persona & rules
Configure tone, form of address, answer length, and prohibited statements.
3
Test in the preview
Run through typical customer questions and check the fallback and handoff behavior.
4
Roll out gradually in the inbox
Start with shadow, approve in copilot, and only then raise selected clusters to autopilot.