AI Assistant for Customer Support Calls: Answer Clients in Seconds

Why live calls are the hardest support channel

Most support tooling was built for asynchronous work. A ticket can wait ten minutes while an agent searches the knowledge base, pings an engineer in Slack and rewrites the reply twice. Phone and video support remove that buffer, and that is exactly where customers judge you hardest.

Three things go wrong on calls again and again:

• Technical depth on demand. A client on a call asks about rate limits, SSO, an error code or an integration edge case. A tier-1 agent knows the answer exists somewhere but not the exact wording, and "let me check and get back to you" turns a five-minute call into a two-day ticket.
• Policy questions under pressure. Refunds, upgrades mid-cycle, data deletion, SLA credits. A wrong answer here is expensive because the customer remembers what you said, not what the policy page says.
• Nobody remembers the last call. The account had a call two weeks ago where someone promised a fix by the next release. The agent on today's call has no idea.

An AI assistant for support calls should fix all three without forcing the customer to talk to a bot. That is the job Kalfi is designed for.

How Kalfi works during a support call

1. Before the call, the agent opens a Client meeting session and fills in the client name, the product area and the facts that matter: plan limits, known issues, policies, escalation rules. This takes a minute when you keep a ready-made context per product.
2. During the call, Kalfi listens to the call audio (and, in Both mode, to the agent's microphone on a separate lane). The live transcript shows each line labelled as Client or You.
3. When the client asks something, Kalfi detects the question and writes a first line you can say immediately, with two or three supporting points below it. Length and tone are set per session, so a quick billing call and a formal incident review do not sound the same.
4. If the line was noisy or the client rambled, press Mic Ask and restate the question in your own words. Kalfi treats that as your restatement of the client's question, matches it against what the client just said and answers the real question.
5. After the call, press Summary. You get an overview, key points, decisions and commitments, and open questions with next steps, ready to paste into the ticket or CRM.

Technical questions: what a good answer looks like

Say a SaaS customer on a video call says: "Our webhook calls started failing with 429 since yesterday, did you change something?" Without help, a tier-1 agent either guesses or escalates. With the right context loaded, Kalfi drafts something like:

A 429 means the webhook endpoint is hitting our rate limit. On your plan that's 100 requests per minute. Nothing changed on our side yesterday, but if your traffic grew, the quick fix is to batch events or enable retries with backoff. I can also check if an upgrade to the next tier makes sense for your volume.

Every fact in that answer, the limit, the "nothing changed" status, the upgrade path, came from the session context the team wrote. That is the important design choice: Kalfi is not inventing your product. It turns your own documentation into a sentence the agent can say in the moment.

What to paste into the context for technical support:

• Plan limits and quotas, written as plain facts ("Pro: 100 requests/minute, 10 GB storage").
• Known issues and current incidents, with the approved customer-facing wording.
• Top 20 error codes or symptoms and the first fix for each.
• Integration notes: supported versions, SSO providers, API authentication.
• Escalation rules: when to promise a callback and who owns what.

Billing, refunds and the uncomfortable questions

Support is not only technical. Some of the hardest moments are commercial: a client asking for a refund outside the window, a discount, or why their invoice doubled. Here the value is less about knowledge and more about saying the right thing calmly.

Put your refund policy, upgrade rules and the approved goodwill options into the Talking points field. Set tone to Neutral or Formal. When the client pushes, Kalfi drafts an answer that stays inside policy, acknowledges the frustration and offers the next step, instead of the agent improvising a promise the finance team will have to walk back.

Support in more than one language

Set the meeting language per session and Kalfi writes the suggested reply in that language, including English, Indonesian, Spanish, Portuguese, Vietnamese, Japanese and more. This is useful for teams that support international clients with agents who are fluent but not native: the agent understands the question, and Kalfi helps with clear, professional phrasing in the client's language.

Customer success and account calls

The same setup works for onboarding calls, quarterly business reviews and renewal conversations. Sessions live in project threads, so the next call with the same account starts with the same context and the summaries of earlier meetings are one click away. When a client asks "what did we agree last time?", the answer is in the thread instead of in someone's memory. For the full client-meeting workflow, see AI assistant for client meetings.

Rolling it out to a support team

1. Start with one agent and the trial. Every account gets 3 days with Hosted AI included, no card. Run it on real calls and note where answers were wrong or vague.
2. Write one shared context document per product. Plain facts, policies and fixes. Each agent pastes it into their session, so everyone answers from the same source.
3. Pick answer length. Brief works best for phone support; Balanced for technical video calls.
4. Use Summary for handoffs. Paste the summary into the ticket so the next agent knows what was promised.
5. Move to the Team plan when it sticks: three hosted seats on one invoice for $49/month. Need more seats? Email hello@kalfi.app.

Kalfi vs other ways to get help on calls

Privacy and what the customer sees

Kalfi runs on the agent's computer and listens to the call audio locally. No bot joins, and the overlay window is protected from screen capture on supported systems, so it should not show up when the agent shares their screen. Kalfi does not save audio recordings: short chunks of audio are sent to the speech-to-text model to be transcribed. On the BYOK plan your own OpenAI or OpenRouter key is stored encrypted on the device.

Follow your company's rules and local law about transcribing calls, and do not paste customer data into the context that your policy says must not go to an AI provider.

What Kalfi does not do

• It does not create tickets, update a CRM or reply to emails and chats on its own.
• It does not keep a full verbatim recording of the call. The summary is built from the questions and answers captured during the session.
• It does not have a shared team knowledge base yet; each agent pastes the team's context document into their own session.
• It is a desktop app. Calls on a mobile phone are not captured unless they play through the computer.

Pricing

Hosted seat

$19 / mo

AI included, nothing to configure. $180/year.

Team

$49 / mo

Three hosted seats on one invoice.

Prefer your own AI account? The BYOK plan is $14/month with your OpenAI or OpenRouter key. One important call only? A Single Session pass is $9. Every new account starts with a 3-day free trial with Hosted AI included, no card required. See all plans.

Questions