Agentic commerce

Meet Mercury

Aquerius Mercury gives you a single-pane view into your business and lets you assign and manage key retail operational workflows through agents. Your team works side by side with Aquerius Agents, letting them handle the easy, time-consuming tasks so your team can focus on strategy.

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the challenge

The Q4 Cliff

01

Most of the year's business happens in Q4, but the decisions that decide it are made months earlier.

Signal Blindness

02

Demand shifts show up online weeks before sales data catches up, and by then it's too late to act.

Cold Start Problem

03

Forecasts require historical trends. That's hard when you're launching something new.

retail intelligence

Agentic Operating System for Retail

Every morning, Mercury briefs you on how business is going, what risks it foresees, and what needs a decision.

Unified AI Intelligence

24/7 AI agents continuously deliver tailored insights in a single, unified view.

End-to-End Demand Planning

01

Navigate every step of demand planning, from signal to allocation, with agents working alongside your team. Leave the busywork to agents, focus on strategy with your team.

New Product Introduction (NPI)

02

Forecast new products from day one, no sales history required. The analogue-based NPI system delivers a demand range and production recommendation before the first unit ships.

Synthesized View of Channel Trends

03

Consolidate trends from various channels, including social media, to accurately assess demand and interest. Turn those insights into action.

Persona-Specific View

04

Each member of your team sees the business from their perspective, tailored to their responsibilities. The room debates strategy, not whose numbers are right.

ARCHitecture

Why Mercury Works

Aquerius is built on knowledge graphs, ontologies, and temporally grounded reasoning. Your data isn't just ingested and presented in charts, it's reasoned through and constantly evolving with real-time signals organized by Aquerius Agents.

Knowledge Graphs

Aquerius connects every piece of your business data to everything it relates to, instead of leaving it siloed in rows and columns.

Ontologies

Domain-specific ontologies teach Aquerius the actual structure of your business and industry, not just the words in your data.

Temporal Grounding

Every fact carries a timestamp, so Aquerius Agents can trace how and when something changed, not just what it is now.

Frequently Asked Questions

01 How can you forecast a new product with zero sales history?

We use analogue-based forecasting. Describe the new product's attributes, material, age range, category, SKU type, and we pull demand trajectories from comparable products already in the corpus. That builds a demand range and production recommendation, ready before you ship the first unit, no sales history required on your end. Underneath, semantic search, our category graph, and live trend signals set the priors, then a Bayesian model runs the actual forecast.

02 What's a temporal knowledge graph?

A temporal knowledge graph is a knowledge graph where every fact carries a timestamp for when it became true, and, if relevant, when it stopped being true. That distinction is important because relationships between things change over time and a system that only stores the current state loses the ability to reason about trends, causes, or what changed and when. Mercury is built on exactly this kind of graph, which is what lets it reason about how demand shifts over time instead of just reporting what happened last.

03 How is this different from a better spreadsheet or BI tool?

Most tools bolt workflows onto your existing data. We built the reasoning layer first, a knowledge graph that understands what your data actually means (a SKU, a channel, a lead time), not just how to store it. That's why we can do what a spreadsheet or BI tool can't: forecast something you've never sold before, catch a trend before it hits your sales numbers, and factor in different lead times and margins across channels, all without someone rebuilding the logic by hand. The forecast updates the moment new signals come in, no one has to refresh a report. Every fact carries a timestamp, so the reasoning always knows not just what's true, but when it became true.

05 Do I need a dedicated demand planner to use this?

You don't need to be a demand planner to use Mercury. In fact, we make demand planning easy for anyone on the team by running multiple algorithms based on product history, category, and channels.

06 What happens to accuracy as I use it over time?

It gets better. Each product you launch through Aquerius sharpens the model for your specific catalogue, so accuracy builds with every new SKU instead of staying flat.

07 Why not just build this in-house?

Building this in-house means solving problems we've already spent time on. You'd need a knowledge graph and ontology layer, a corpus of comparable products deep enough to forecast a product with zero sales history, pipelines that pull live signal from social media, and a Bayesian model that updates forecasts weekly instead of waiting on a full sales cycle. Most teams building this from scratch will spend extensive time and money, Mercury connects in under 24 hours and starts forecasting immediately, at a fraction of what that build would cost in engineering time alone.

Pricing

Pricing Built Around Your Catalog

Mercury pricing depends on your SKU count, channels, and complexity. There's no one-size-fits-all rate. Tell us a bit about your business and our team will follow up with a quote tailored to you.

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