FOR POST-SALE TEAMS
Post-sale decides whether a customer returns. The best of that team, cloned: orders, returns, invoicing.
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“The entire post-sale journey is handled by Eva, our StudioChat assistant, connected to Amazon, Mercado Libre, our official store and WhatsApp. The team now focuses on the cases that truly need them.”
Order status, returns and invoicing don't stop at 6pm — and they spike hardest during peak season, exactly when your team is stretched thinnest.
The bulk of the day’s volume: where is my order and where is my invoice. Two questions answered from the OMS and the carrier, not from a ticket queue.
Pulls live carrier and OMS data to answer "where's my order" the instant it's asked — no ticket, no wait.
Handles compliant invoice requests end to end — a high-effort, repetitive ticket type across LatAm.
Returns & exchanges: Walks the customer through eligibility, generates the label, and confirms next steps.
Warranty claims: Diagnoses the issue, checks coverage, and starts the claim without a back-and-forth.
Payment disputes: Handles chargebacks and billing disputes with the transaction data already attached.
Post-purchase upsell: Suggests the complementary product or the upgrade in the same conversation.
Answers wherever the customer already reached out, in one consistent voice.
Absorbs seasonal volume without a seasonal hiring plan.
Most post-sale tools stop at "where's my order." We start from the person on your team who already resolves returns, invoicing and disputes well, and clone the whole journey.
We capture how the best post-sale rep already resolves a delayed order or a return — tone included — and layer in the best practices we've seen across post-sale, by industry.
Tracking, returns, invoicing, warranty and disputes in one assistant, not five point tools each owning one step.
Same context and tone regardless of which channel the customer picks — and no seasonal hiring plan needed for peak.
LLM security, agent security, client control, and infrastructure aren't the same layer — each protects something different, and the agent leaves a trail of everything it does along the way.
A language model can make the wrong call — delete something it shouldn't, invent data that doesn't exist (like a bank account number), or let spend spiral out of control. Guardrails validate what the agent is about to answer before it answers, automatically or manually, covering hallucinations and prompt injection.
Every integration goes through a middleware layer the client configures — StudioChat can't see the data the client chooses not to share. Control stays on the client's side, by design.
The most common fear is that the agent does something and no one finds out. That's why every answer comes with its reasoning and its citations — no black box acting without leaving a trace.
Any ticket type that shows up after checkout — for example: order status and shipping, returns and exchanges, invoicing, warranty claims, and payment disputes. Actual coverage depends on the playbooks the assistant is trained on, not a fixed list.
No. StudioChat plugs into the helpdesk you already run — Intercom, Zendesk, or whichever you use — as a non-human agent, not a replacement platform.
Yes. Invoicing is a good example — it varies by country (like SAT rules in Mexico) and requires integrating with the systems already in use — but the same approach applies to any task that depends on an external tool or a specific local rule. It's configured per customer, end to end, the same way it runs for Avera.
Outcome-based: you pay per resolved task, not per seat, not for setup.
Yes — Avera (avera.mx), a Mexican ecommerce brand, runs its entire post-sale journey (invoicing, tracking, shipping, returns) on a single StudioChat assistant.