Context layers and execution layers solve different problems.
Both sit in the AI-for-supply-chain category. They are not the same thing, and they are not built for the same customer. This page defines both honestly and compares them fairly, so a distributor can tell which one actually fits.
Context layer
Unifies data you already have (orders, inventory, sales, suppliers) into a single, governed layer that AI tools can query, typically through a protocol such as MCP. It makes your data legible to AI. It does not decide or act on your behalf; you bring the AI tools.
Execution layer
Reads from your operational systems, decides what to do, does it, and logs the result, with a human checkpoint where trust or money is at stake. It is not a dashboard. It is not an inbox. It is not a chatbot. Conducta is an execution layer, built for wholesale distributors.
A fair comparison
We compare against the context-layer category rather than any single vendor. The context-layer column describes how these products generally position themselves. We make no pricing, feature or performance claim about any specific competitor.
| Dimension | Conductaus Execution layer for wholesale distributors | Context layer Typically built for AI-native CPG brands |
|---|---|---|
| Who it's for | Wholesale distributors | CPG brands (manufacturers) |
| What it does | Reads, decides, executes and checkpoints the work end to end | Unifies data into a single governed layer |
| AI tools | Built-in agents with human-in-the-loop approval | Bring your own, connected via MCP |
| Integrations | UK distributor stack: Bevica, Xero, and more | Connects your orders, inventory, sales and supplier data |
| Proof | Published own-P&L results from a real wholesaler | Customer logos published on their site |
| Where the work happens | In Slack, where your team already works | In the AI tools you bring |
Which do you need?
You are a brand
If you manufacture product and want your data made legible to AI tools you already have or plan to build, a context layer fits that job. That is what context-layer products are built for.
You are a distributor
If you sit between suppliers and trade customers and want orders, stock, invoices and customer chat actually handled, not just made visible to AI tools you bring yourself, you need an execution layer. That is what Conducta is built for.
Read more on why Conducta is built for distributors, not brands, in our positioning piece.
Questions
What is the difference between a context layer and an execution layer?
A context layer unifies your data (orders, inventory, sales, suppliers) into a single, governed layer that AI tools can query, typically through a protocol such as MCP. It does not act on your behalf; you bring the AI tools. An execution layer reads from your operational systems, decides what to do, executes it, and checkpoints with a human wherever trust or money is at stake. Conducta is an execution layer built for wholesale distributors.
Is Conducta an alternative to a context layer?
Not directly. Context layers are typically built for CPG brands: they unify brand data and expose it to AI tools you bring. Conducta is an execution layer for wholesale distributors: it reads, decides, executes and checkpoints with human approval, built and proven inside a real UK wholesaler. The two target different customers (brands vs distributors) and solve different problems (data unification vs end-to-end execution), even though both sit in the AI-for-supply-chain space.
What is a context layer, exactly?
A context layer unifies a company's data (orders, inventory, sales, suppliers) into a single, governed layer that AI tools can query, typically through a protocol such as MCP. In the CPG space these products are generally built for brands (manufacturers), with use cases such as category management, demand forecasting, inventory management and promo ROI. The point is that a context layer makes your data legible to AI; it does not do the operational work for you.
Can a distributor use both a context layer and an execution layer?
Yes, in principle. A context layer and an execution layer solve adjacent but different problems, so there is no structural conflict in running both. In practice, most wholesale distributors we talk to want the work done rather than data made available to AI tools they would then need to build or buy separately, which is why Conducta ships as a complete execution layer rather than a data layer alone.
Which one do I need?
If you are a brand that wants your data made legible to AI tools you already have or plan to build, a context layer fits that job. If you are a wholesale distributor and want orders, stock, invoices and customer chat actually handled, with a human checkpoint on anything that touches price, credit or trust, you need an execution layer. That is what Conducta is built for.
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