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For Ecommerce agencies
An ecommerce agency running paid acquisition for ten to fifty DTC client accounts has a multiplexing problem. Each brand needs its own fine-tuned product identity, its own variant cadence, and its own approval chain. Generic AI tools force the agency to manage that across as many tabs as it has clients. Avocado AI is the workspace built around the agency-of-many-brands model.
An ecommerce agency wins or loses on creative velocity per client account. The faster the variant cadence, the more performance data, the better the optimization. The trap is that velocity collapses the moment brand fidelity starts drifting. A skincare client expects their bottle. A supplement client expects their canister. A fashion client expects their cut. Generic AI tools cannot keep all of those locked while the agency multiplexes across accounts.
Avocado AI is built around brand fine-tuning, which is the load-bearing feature for an agency operating across many accounts. Each client gets its own fine-tuned model inside the agency workspace. Every variant generated for that client locks the brand identity. The variant cadence stays high without the fidelity drift that kills generic-AI ad creative.
Inside Avocado, each client account has its own Storyboards canvas, its own fine-tuned image models on the client product line, and its own pool of variants. The agency operator multiplexes across canvases without leaving the workspace. The Lini agent holds brand context per client, so switching from a skincare client to a supplement client does not require re-explaining the brief to the agent.
Upload twenty to forty product photos per client. Avocado fine-tunes any of nineteen image models on each client is line. The fine-tuned model becomes a persistent brand identity for that client. Every generation locks label text, pantone, and silhouette. The client sees consistency across hundreds of variants without the agency hand-editing every output.
Different clients need different video cuts. The cinematic pack shot for the supplement client. The stylized 9:16 social for the fashion client. The brand film for the skincare client. Avocado runs Seedance 2.0, Kling, Veo 3, Sora, and LTX-2 in the same workspace, so each client uses the right model per cut without the agency standing up a separate tool stack per account.
The agency-client review loop is one of the biggest time sinks in ecommerce paid acquisition. Avocado runs Storyboards as a multiplayer infinite canvas. The agency operator and the client open the same canvas, comment on frames, and approve variants live. The Lini agent generates new variations on demand when the client wants a tweak.
For an agency running weekly cycles across ten clients, the live canvas removes the Slack, email, and Loom handoffs that usually eat a full afternoon per client per week.
Each client ad needs voice and music. Avocado includes voice generation, voice cloning, AI music, and the Music Studio inside the same workspace. The cloned voice can be unique per client. Compose finishes the cut and exports platform specs for TikTok, Reels, YouTube, and Shopify per client.
Avocado starts at nineteen euros per month, pools credits across image, video, music, and voice, and includes commercial rights on every plan. For an agency running ten DTC client accounts that each need stills plus video plus voice plus music, one Avocado plan typically replaces ten stacks of an image tool plus a video generator plus a music app plus a voice tool plus an editor. The savings compound with each new client.
An agency operator running five to ten client accounts inside a fragmented tool chain usually spends two to four hours per client per week on tool-switching, version drift, and review handoffs. Inside Avocado, that collapses to one workspace per client, one Storyboards canvas, and one Lini agent context per brand. Operators typically save eight to twenty hours per week by week three. The saved hours go back into more variants per client, which feeds the performance loop directly.
The pooled credit model means that adding a new client account inside Avocado does not require buying a new image tool, a new video tool, a new music app, a new voice tool, and a new editor. The new client is a new fine-tuned model and a new Storyboards canvas inside the existing plan. For an agency adding two or three clients per quarter, the savings compound substantially against the standard one-stack-per-client model.
Agency creative has to survive Meta, TikTok, and Shopify content review across every client. Brand fine-tuning per client reduces the inconsistency flags that show up when an agency uses generic AI tools. Commercial rights on every Avocado plan remove the rights-violation flags that show up when teams use tier-gated tools.
Yes. Each client has its own Storyboards canvas, its own fine-tuned image models, and its own pool of variants. The agency operator multiplexes across canvases without leaving the workspace. The Lini agent holds brand context per client.
Upload twenty to forty product photos per client. Avocado fine-tunes any of nineteen image models on that client is line in minutes. The fine-tuned model becomes a persistent brand identity for that client. Every generation locks label text, pantone, and silhouette specific to that brand.
Yes. The agency operator shares the canvas with the client. Comments and approvals happen in real time. The Lini agent generates new variations on demand when the client wants a tweak. The Slack-and-email review loop is removed.
Image, video, music, voice, and UGC in one workspace, with Lini guiding the work. Start free, upgrade when you are ready to scale.
Yes. Voice generation, voice cloning, AI music, and the Music Studio all sit inside the workspace. The cloned voice can be unique per client. The credits pool with image and video.
Avocado starts at nineteen euros per month, pools credits across image, video, music, and voice, and includes commercial rights on every plan. For an agency running ten clients, one Avocado plan typically replaces ten stacks of separate tools. The savings compound with each new client.
In our experience, yes, especially when the brand-fine-tuned model is the source of the product cuts. Most ad-review flags on AI creative come from inconsistent products. Brand fine-tuning per client removes the inconsistency, and commercial rights on every Avocado plan remove the rights-violation flags.
For most clients, yes. Day one is fine-tuning a brand model on the client is existing product photos. Day two is rebuilding the client is top three ad variants in Storyboards. Day three is adding the cinematic cut and the social cut, then dropping in voice and music. Day four is sharing the canvas with the client for sign-off.