Magnetforce is a private AI layer for Salesforce Sales Cloud, Service Cloud, and Experience Cloud. It adds practical AI use cases to the Salesforce environment your team already uses: account research, pre-meeting briefings, call transcription, conversation summaries, sales reports, and CRM record enrichment.

It is built by Ideaport Riga, a Salesforce implementation partner.

No. Salesforce stays the system of record and the daily work surface. Magnetforce connects to Salesforce through standard configuration artefacts and APIs, so AI-assisted outputs appear inside Sales Cloud, Service Cloud, and Experience Cloud.

No. Magnetforce is positioned as complementary to Salesforce, not as a competitor to Agentforce. It is for organizations that want practical AI inside Salesforce while keeping data, model choice, and orchestration under customer control.

About 50% of agentic AI projects stay stuck in pilot, with security and compliance cited as the primary barriers (Architecture and Governance, 2026). Magnetforce is designed to clear those barriers by running in customer-controlled infrastructure and using customer-approved AI models, so AI projects can move from pilot into production inside Salesforce.

Midsize and enterprise Salesforce customers. The primary buyers and users are Sales Leaders, Service Leaders, Salesforce platform owners, and IT architects who need AI inside Salesforce workflows but want control over data residency, model choice, and cost. It fits especially well in organizations with strict privacy or security review requirements.

Six concrete ways:

Forecast confidence - Deal summaries and risks are grounded in actual calls, activity, and account context.

Pipeline visibility - Reviews focus on real deal movement and commitments rather than dashboard hygiene.

Better meeting prep - Reps get briefings combining Salesforce history and external account signals.

Follow-up discipline - Action items, commitments, and next steps are captured automatically and pushed back into Salesforce.

Salesforce adoption - AI saves rep time inside the tools they already use.

Coaching insight - Risks, objections, and stalled opportunities are visible from real conversation content, early enough to coach the team.

The sales theme is Better Preparation, Better Conversations, Better Follow-Up. Use cases include prospecting and account research, AI account summaries and pre-meeting briefings, call transcription and processing (Teams meetings, audio/video uploads, dictated text), sales conversation summarization, AI assisted sales reports highlighting progress and risks, post-call follow-up support, and Salesforce record enrichment. Outputs go back into Sales Cloud records.

Magnetforce uses standard Salesforce configuration artefacts that connect Sales, Service, and Experience Cloud to the Magnet AI platform via API. A user triggers an action in Salesforce, Salesforce sends record context to Magnet AI, Magnet AI orchestrates the right prompt template, RAG flow, retrieval tool, or agent, an approved AI model runs, and structured output returns to the Salesforce record. Usage, cost, and quality are logged.

Three layers:

Salesforce layer - Sales Cloud, Service Cloud, Experience Cloud. Where users see, trigger, and consume AI-assisted workflows.

Magnet AI layer - A low-code AI orchestration platform with prompt templates, RAG tools, retrieval tools, API and MCP tools, agents, knowledge sources, channels, evaluation, usage analysis, and OpenTelemetry tracing.

AI Models layer - Customer-approved language, speech, and embedding models, deployed locally or in the customer's chosen cloud.

Magnet AI deploys in customer-controlled public cloud, private cloud, or private network environments. For Azure, the documented resources include virtual network, Azure Database for PostgreSQL, Azure Container Apps, Microsoft Foundry / Azure OpenAI as an optional model provider, and Azure Container Registry as an optional container source.

Customer-approved language models, speech models, and embedding models. Magnet AI connects to many LLM providers by storing API keys, capabilities, and costs, and can use either locally deployed LLMs or public cloud models under the provider's security and privacy policies. There is no platform markup on AI model costs.

Magnet AI supports document ingestion, parsing, chunking, vector embedding creation, semantic search, and metadata filtering across sources such as Salesforce Knowledge, SharePoint, HubSpot CMS, Oracle Fusion Knowledge, public file stores, and websites. Custom connectors are supported via OpenAPI v3 or MCP.

Magnetforce runs in customer-controlled environments, so sensitive sales, service, customer, case, and knowledge data do not have to be processed in a vendor-controlled AI environment. This makes enterprise security and GDPR review easier and supports stronger data residency control.

Every LLM call, RAG question and answer, and agent conversation is logged and analyzed by response quality, cost, and latency. Dashboards aggregate performance over time. Technical traces are available in OpenTelemetry format and can be sent to external monitoring tools such as Azure Monitor.

Two main commercial components.

Onboarding: 6,000 EUR one time. All Salesforce configuration artefacts are free; a 2-week onboarding engagement is mandatory.

Infra and AI models: provided by the customer (container runtime, PostgreSQL, and access to AI models). No platform tax on AI model costs.

Magnet AI itself is free and open source. Premium support is available separately and is highly recommended for production use.

The 6,000 EUR is a one-time fee covering the mandatory 2-week onboarding engagement. The Salesforce configuration artefacts themselves are free. The engagement covers Sales Cloud, Service Cloud, and Experience Cloud setup and configuration of the customer's first use cases.

Customers provide a container runtime, PostgreSQL, and access to AI models. Infrastructure runs in the customer's chosen public cloud, private cloud, or private network environment. AI model usage is paid directly to the customer's chosen providers, with no extra platform tax.

Magnet AI is used in production at organizations including Konecranes, GMC, Tet, and LIAA, supporting use cases such as technician Q&A, customer summarization, spare parts search, public information research, customer and employee chatbots, and structured evaluation of applications.

Yes. A pre-recorded demo is available so you can see Magnetforce in action before any sales conversation. Use the See demo button anywhere on this page. No scheduling and no sales call required.