Sales Layer

Connections to named business systems both read and write. Integration runs "with your ERP or CMS" and through "pre-built connectors to marketplaces, selling platforms, third party sites and procurement platforms", syndicating catalogs and updates in real time, with the API "for both data import and export".

Dedicated integration pages cover ERPs (SAP R/3, SAP Business One, JD Edwards, Microsoft Business Central, Cegid Ekon, Odoo), CRMs (Salesforce, HubSpot) and commerce and marketplace platforms (Magento, Mirakl). The agents act on the catalog those connectors synchronize, and agents, the REST API and AI automation sit in one flow. Sales Layer describes no credential scoping or rotation. Separately, the MCP Server and REST API make Sales Layer callable from outside.

Sourcesaleslayer.com/enterprise-pim, saleslayer.com sitemap, saleslayer.com/ai-pim/suite; readread 2026-09-15

A builder without code sequences, routes and chains agent steps alongside deterministic rules. It has three stages, a trigger, then conditions that "filter your catalog to target specific products, categories, or attributes" with "control logic with AND/OR operators" for routing, then actions that "chain multiple AI-powered actions" with "sequential execution" and "use results from previous actions", so state passes between steps.

Deterministic and agent steps mix, as Smart Business Rules, whose "rule-based execution ensures predictable, reliable results", chains alongside generative actions. Worked examples chain Create Content, Improve Text and Translate, or Smart Business Rules, Smart Categorizer and Improve Images. Sales Layer describes no retries, fallback paths, versioning or reuse across teams.

Sourcesaleslayer.com/ai-pim/agentic; readread 2026-09-15

Context documents, brand voice and business rules attached to each action ground the agents, but that context is assembled for each run, not through a retrieval layer. Each action can be made a sector specialist by adding "sector-specific context documents (lighting, furniture, nutrition, etc.)", brand voice control (keywords, tone, style guides, writing rules) and business rules, and the agents act on the customer's own product records in the PIM.

New knowledge enters as documents, not retraining. The context documents attached to an action and the item being processed come together fresh for each run, however many sources they draw on. There is no retrieval index over the documents, no retrieval setting and no citation. The PIM catalog itself is the application's data model.

Sourcesaleslayer.com/ai-pim/agentic, saleslayer.com/ai-pim/suite; readread 2026-09-15

Approval happens inside the PIM itself, before changes publish. Review Mode can hold every change for approval before it goes live, and people review, approve or discard changes individually or in bulk, with progress tracking of review status and completion percentage.

Review Mode is optional for each agent, and Sales Layer calls it "perfect for high-stakes catalogs", so a customer can run low risk agents without it and high risk ones with it. Approvals do not route into ticketing tools, and nothing explains why a checkpoint fired. A separate before and after simulation preview supports testing.

Sourcesaleslayer.com/ai-pim/agentic, saleslayer.com/ai-pim/suite; readread 2026-09-15

A held certification sits beside access controls that customers use. Sales Layer holds ISO/IEC 27001:2022 and PCI DSS v4.0.1, listed under Compliance in its SafeBase trust center at trust.saleslayer.com with gated reports and a pentest report, and its product pages repeat the ISO 27001 certification. Customers get access controls as well.

Single sign on protects users, the MCP Server is "deployed with encrypted communication, role-based permissions" and authenticates with API tokens and OAuth 2.0, and multi factor authentication is listed under product security. The internal SSO, least privilege and access control policy in the trust center cover Sales Layer's own staff.

Sourcetrust.saleslayer.com, saleslayer.com/enterprise-pim, saleslayer.com/ai-pim/mcp; readread 2026-09-15

Customers can see what each agent changed and how review is progressing, but there is no run history to inspect afterward. Review Mode tracks progress ("monitor review status and completion percentage in real-time"), and each change has a before and after view of what an agent modified. Audit logging is listed under product security in the trust center, and the MCP Server offers real time monitoring.

The review list shows pending changes before publication, progress percentages are aggregate, and the audit logging entry is a heading whose detail sits behind the trust center's access gate. There is no readable run history of agent executions with the steps taken and tools called. Catalog quality scores measure the customer's data, not the agents.

Sourcetrust.saleslayer.com, saleslayer.com/ai-pim/agentic, saleslayer.com/ai-pim/mcp; readread 2026-09-15

Agents keep no memory across runs. What persists is configuration people write, namely context documents, brand voice and business rules. Those are instructions the product applies, kept because a person wrote them down, not because the agent retained anything, and the product records the agents act on are the application's own database. The one piece of run state, "use results from previous actions" within a chain, lasts for a single execution. With no memory across runs, there is nothing to review, edit, delete or scope.

Sourcesaleslayer.com/ai-pim/agentic; readread 2026-09-15

The platform runs as a single hosted service on Amazon Web Services, with a separate production environment and an alternate processing and storage site for continuity. No region is named, no customer environment or region selection is offered, and nothing lets a customer pin storage or model traffic to a region.

Local deployment is offered for the MCP bridge ("run your AI stack without sending a single file outside your infrastructure"), but that installs the connector between the customer's AI tools and Sales Layer's API. The PIM and its data stay on Sales Layer's hosted service, so the bridge is not a deployment mode for the product.

Sourcetrust.saleslayer.com, saleslayer.com/ai-pim/mcp; readread 2026-09-15

Prebuilt agents are named, each with its own page.

Pages at /ai-pim/agents/content-creation, /translation, /product-data-quality and /category-taxonomy each carry a description and an "Explore the agent" link, covering Content Creation (descriptions, marketing copy, SEO content), Global Translation (50+ languages with local variants) and Smart Business Rules (natural language validation and transformation), plus Smart Categorizer and Improve Images actions, with worked Content Specialist and Data Quality agents.

Each does a whole job on its own. They are editable, since each action can become a sector specialist with industry context, brand voice and business rules added. Sales Layer gives no customer references for each agent.

Sourcesaleslayer.com/ai-pim/agentic, saleslayer.com sitemap; readread 2026-09-15

Work reaches Sales Layer's agents without a person starting it, on catalog events and schedules. The builder's first step sets when the agent acts, on item creation or update, on a daily or weekly schedule, or on demand by hand. Conditions filter which products a trigger acts on, with category, product type and attribute filters and AND/OR logic. Sales Layer describes no messaging, email or webhook channels, and no handling of duplicates or races. The MCP Server also lets external agent frameworks monitor catalog changes.

Sourcesaleslayer.com/ai-pim/agentic; readread 2026-09-15

Customers get no model choice for the platform's own agents. No model is named for the agents, the AI Suite or the MCP Server, and there is no selector, routing disclosure or way to bring your own key.

The "Works with your favorite AI tools" list (Claude Desktop and API, Microsoft Copilot Studio, OpenAI ChatGPT and API, Google Gemini, Cursor, VS Code and Mistral open models) names tools a customer uses to call Sales Layer through the MCP Server and REST API, not models the platform's agents run on.

The Expert GPTs (Data Macros GPT, Template Builder GPT) are assistants published inside ChatGPT, also not a model choice for the platform's agents.

Sourcesaleslayer.com/ai-pim/suite, saleslayer.com/ai-pim/agentic, trust.saleslayer.com; readread 2026-09-15

A read and write MCP server sits on top of Sales Layer's API. The server runs hosted at mcp.saleslayer.com or as a local installation, authenticates with an API token or OAuth 2.0, and comes in two modes, a "read-only server" and a "read/write server" that can "create new product records, update prices or descriptions in bulk, and synchronize catalogs", "designed for integration with agent-based systems". An API sits underneath.

The MCP Server is "a standardized bridge between AI-powered tools and your Sales Layer API", Sales Layer invites customers to "build on top of our API to create your own custom integrations, for both data import and export", and a "REST API for custom integrations" is listed, with documentation linked from the MCP page. n8n, Make, Zapier and custom agent frameworks are named consumers. No SDK is named. Claude, ChatGPT, Gemini and Mistral appear as tools that call Sales Layer, not as models its agents use.

Sourcesaleslayer.com/ai-pim/mcp, saleslayer.com/enterprise-pim, saleslayer.com/ai-pim/suite; readread 2026-09-15

A customer can test an agent on sample data before it runs on the catalog, and gets a preview, not a scored result.

The product has customers "validate your agent's configuration with real product data before running it on your entire catalog", through Simulation Mode, which tests actions on sample items without affecting real data, a before and after preview comparing original and modified values side by side, and iterative refinement ("adjust configuration and re-test until perfect").

The preview shows the changes a configuration would make for a person to inspect. It produces no score, pass rate or judge verdict. There is no scoring of quality over time and no optimization loop after deployment.

Sourcesaleslayer.com/ai-pim/agentic; readread 2026-09-15

Every action operates on product records inside the PIM, and every outside system is reached through connectors, the REST API or the MCP Server, so there is no browser or computer control. Improve Images edits product image files, which is content work, not computer control.

Sourcesaleslayer.com/ai-pim/agentic, saleslayer.com/ai-pim/mcp; readread 2026-09-15