An always-on intelligence layer that audits your clients' storefronts at scale. Behind it sits a multi-agent pipeline of headless crawlers, vision-language models, fine-tuned domain classifiers and dedicated retrievers — coordinated by Maestro, a large-context orchestrator that routes evidence between specialists, validates output and signs off the brief.
Every morning, Maestro scans every store you manage, dispatches each finding to the right specialist agent, and ships the conclusions as branded, ready-to-send recommendation emails under your agency's identity.
Each agent owns a single domain and a tailored stack — crawlers, custom-trained classifiers, vision-language models, retrievers, statistical engines. Maestro dispatches the audit, gathers the evidence, validates it, and writes the brief that lands in the merchant's inbox under your brand.
A headless crawler renders every page after JS hydration and walks the full link graph. Hard 4xx, soft-404s and silent redirects are discriminated via content fingerprinting. Each break is weighted by its position in the graph — canonical paths, sitemap presence, inbound anchor count — so the merchant receives a ranked triage rather than a flat error log.
Reconciles the public review stream with the moderation backlog to surface 4–5 star feedback the merchant never released. A sentiment-and-authenticity classifier filters spam, low-effort and incoherent submissions before the agent flags genuine reviews ready for one-click publication.
A multilingual identifier scores every visible text node on the homepage against the configured store locale, isolates legitimate code-switching (brand names, foreign trademarks, catalog-driven titles) and flags genuine drift. Maestro cross-references the result with the store's catalog and copy history before raising the signal.
Multi-pass audit over the rendered DOM: structured-data validation, heading hierarchy, internal-link entropy, Core Web Vitals proxies and intent-coverage analysis against the merchant's own catalog vocabulary. The agent surfaces the gap between what the homepage says and what the catalog actually sells — the highest-leverage SEO move most stores never make.
A locale-aware language model performs orthographic and grammatical inference on every static page. A pre-classifier mask removes proper nouns, brand entities and SKU references before the model runs, eliminating false positives at scale. Findings are confidence-scored, deduplicated across pages and delivered with surrounding context so the fix is one click — not a hunt.
A change-point detector runs over the rolling rating distribution, distinguishing organic decay from genuine inflection. Maestro correlates the inflection with concurrent signals — review velocity, channel mix, payment-failure spikes — to attribute the cause before alerting, so the brief lands with the why, not just the what.
Surfaces 1–2 star feedback the merchant chose not to publish. A fine-tuned response generator, conditioned on the reviewer's tone and the actual complaint vector, drafts a brand-safe reply — routed by Maestro through a tone-and-policy validator before it reaches the merchant's inbox. Empathetic, on-brand, ready to send.
Walks the category tree, computes density and depth metrics per node, and benchmarks against vertical baselines learned across the multi-tenant fleet. Empty taxonomic branches and orphan categories are flagged with their estimated SEO and conversion cost — turning a structural defect into a prioritised fix list.
Probes each social profile linked from the storefront, extracts last-activity timestamps and engagement decay curves, and flags accounts whose silence is hurting brand credibility. Distinguishes legitimate seasonal pauses from genuine abandonment via the merchant's own posting history.
A vision-language model performs cross-modal alignment between hero creatives, homepage copy, and a calendar of commercial windows — Black Friday, regional festivities, sales cycles — augmented with the merchant's own historical lift signal. Maestro raises the flag before the window closes, not after.
A statistical CRM intelligence layer operating over the merchant's full order graph. Seven specialised analyses run in parallel — behavioural cohort scoring, market-basket co-occurrence mining, time-series anomaly detection, year-over-year window matching, multi-touch channel attribution, gateway success-rate analysis and postal-to-province geographic enrichment. Maestro fuses the seven outputs into a single decision-grade brief and routes it for delivery. The language model writes; the analysis is rigorous algorithmic work.
source[] array.> 1,247 orders analysed · revenue €84,330 · avg. order €67.63 > 12 Champions concentrate 38% of revenue (€32,044) > Positive anomaly: Apr 14 · 89 orders (3.1× baseline) > Cross-sell: "Hauck Crib" + "Fleece Footmuff" (× 17 baskets) > > Recommended action: email 47 customers in Opportunity cohort > · estimated recovery €6,200 · restock 6 cross-sell SKUs.
// example output · real briefs are tenant-specific and arrive in your white-label inbox
A dedicated retrieval agent ingests the merchant's Shopping feed and joins it against Google's own demand and competitive-pricing signals. A fine-tuned listing classifier scores every product on title quality, description completeness and competitive price position, then cross-references high-demand SKUs with their actual visibility in the SERP. Maestro ranks the result by recoverable revenue, so the merchant sees first the listings that are one fix away from converting.
Every client storefront is swept daily by the agent fleet. Findings are deduplicated across runs, scored against tenant-specific baselines and ranked by recoverable revenue before they ever reach a human.
Each finding is rendered into a tenant-themed HTML email — your colors, your domain, your sender identity — and dispatched through your authenticated SMTP. The attention to detail looks like yours.
Per-tenant cooldowns, severity-weighted suppression and time-of-day windows prevent inbox fatigue. Maestro decides what to send, when, and what to hold for the next sweep.
Your team gets a single morning summary across all tenants: what was found, what shipped, what's queued. The proactive work is done before the standup begins.
Strict tenant isolation, per-tenant model conditioning, shared inference fleet. Scales from ten storefronts to hundreds with linear cost and zero operational tax — onboarding is configuration, not engineering.
Reactive client management becomes continuous, instrumented optimization. The agency moves from invoicing time to invoicing outcomes — a pitch, a retainer, and a moat in one motion.
Reactive client management is over.
Maestro conducts. The agents work.
Your retainer compounds.