Connect customer data, teams and intelligent workflows.
Current, practical delivery across Data 360, Agentforce 360, Marketing Cloud, Account Engagement, Sales Cloud, Service Cloud, MuleSoft and analytics.
The Salesforce Products We Work On
Salesforce has renamed a lot recently — Pardot is Marketing Cloud Account Engagement, Data Cloud is Data 360, and Agentforce branding now runs across the clouds. Here is what that means in practice.
Marketing Cloud (Agentforce Marketing)
What it is: Salesforce's marketing platform, sold today as Marketing Cloud Growth and Marketing Cloud Advanced editions and branded Agentforce Marketing, alongside the established Marketing Cloud Engagement estate.
What we do: Journey and campaign design, data extension and automation architecture, email and SMS build, AMPscript and SQL work, deliverability remediation, and migration from legacy Engagement orgs onto current editions.
Data 360 (formerly Data Cloud)
What it is: Salesforce's data engine, unifying enterprise data into real-time profiles — including Zero Copy access to your warehouse rather than duplicating data.
What we do: Data stream and connector setup, identity resolution rules, calculated insights, segmentation, Zero Copy patterns with Snowflake or BigQuery, and activation into marketing, sales, and service.
Marketing Cloud Account Engagement
What it is: B2B marketing automation, the product previously called Pardot, now with an Account Engagement+ tier that adds Data 360 and agentic capability.
What we do: Engagement Studio programmes, scoring and grading models, form and landing page frameworks, CRM sync hygiene, and consolidation when Account Engagement and Marketing Cloud both exist.
Sales Cloud
What it is: Core CRM for sales, now fronted as Agentforce Sales with AI agents across prospecting, pipeline, and forecasting.
What we do: Object and process design, sales engagement cadences, forecasting configuration, conversation insights, data quality programmes, and integrations to marketing and finance systems.
Service Cloud
What it is: Omnichannel customer service with an AI layer for case deflection and resolution, plus Field Service for on-site work.
What we do: Case and routing design, console layouts, knowledge base structure, self-service portals, and AI deflection where the knowledge content genuinely supports it.
Agentforce 360
What it is: Salesforce's platform for autonomous AI agents, using hybrid reasoning across deterministic logic and language models, built with Agentforce Builder and Agent Script.
What we do: Use-case selection, agent and subagent design, action and permission modelling, grounding against Data 360, evaluation and guardrails, and Agentforce for Slack deployments.
Salesforce Personalization
What it is: Real-time cross-channel personalisation and decisioning, formerly Marketing Cloud Personalization (Interaction Studio).
What we do: Catalogue and identity setup, campaign and recipe configuration, web and app SDK implementation, and joining personalisation signals to your Data 360 profiles.
Marketing Cloud Intelligence
What it is: Marketing analytics and reporting across channels and ad spend.
What we do: Data harmonisation across sources, dashboard and metric design, and cost and performance reporting that finance and marketing can both agree with.
Commerce Cloud
What it is: B2B and D2C commerce, with Agentforce Commerce extending catalogues and checkout into AI-driven shopping channels.
What we do: Storefront implementation and extension, catalogue and pricing configuration, order management integration, and connecting commerce events into marketing journeys.
Experience Cloud
What it is: CRM-powered portals, communities, and branded sites built with Experience Builder.
What we do: Customer and partner portal builds, LWR site development, CMS workspace structure, sharing and access design, and performance tuning.
MuleSoft and integrations
What it is: Anypoint Platform for API design and management, now also positioned as the control plane for governing APIs and agents.
What we do: API-led integration design, reusable API assets, error handling and monitoring, and pragmatic alternatives when MuleSoft is heavier than the problem requires.
Analytics and trust
What it is: Tableau and Tableau Next for agentic analytics on the Data 360 semantic layer, and the Einstein Trust Layer for masking, grounding, toxicity scoring, and audit trails.
What we do: Semantic model design, dashboard delivery, embedded analytics, and trust-layer configuration and documentation for security and compliance review.
How a Salesforce Engagement Runs
Structured delivery with your admins and architects involved from the first workshop.
Org and data assessment
We review your org configuration, data model, automation debt, integrations, and licence usage, and hand back a written picture of the current state with prioritised risks.
Solution design
Data model changes, identity resolution rules, journey and process designs, integration contracts, and a release plan agreed before build starts.
Build and test
Iterative delivery in sandboxes with documented configuration, deployment via source control where your org supports it, and UAT scripts your team can rerun.
Data quality
Most Salesforce problems are data problems. Deduplication, validation, consent capture, and unification rules get treated as first-class work, not clean-up at the end.
Enablement
Admin, marketer, and analyst training plus runbooks for the journeys, automations, and agents we build, so your team can change them safely.
Ongoing support
Release readiness across Salesforce's three annual releases, monitoring, backlog delivery, and periodic reviews as products and naming continue to change.
Salesforce Questions We Are Asked Most
Is Pardot gone?
Only the name. The product is Marketing Cloud Account Engagement, with an Account Engagement+ tier layering in Data 360 and agentic features. Existing implementations continue to work; the decision is usually whether to stay on it or consolidate into Marketing Cloud Growth or Advanced.
What changed with Data Cloud becoming Data 360?
The positioning more than the mechanics: it is the data foundation the rest of the platform and Agentforce depend on. If you plan to use AI agents seriously, identity resolution and data governance in Data 360 are the prerequisite, not an optional phase two.
Should we adopt Agentforce now?
For narrow, high-volume, well-documented processes, it can pay off quickly — service deflection against a solid knowledge base is the clearest case. We start with one use case, measurable outcomes, and explicit guardrails, and we are candid when a simpler automation would do the same job for less.
We are on Marketing Cloud Engagement. Do we have to move?
Not immediately. We map what your current journeys, automations, and integrations actually do, then compare that against the current editions so the decision is based on your footprint rather than a sales deck.
Can you work alongside our in-house Salesforce team?
Yes. Most of our engagements are joint delivery — we bring specialist depth on Marketing Cloud, Data 360, or Agentforce and work inside your existing release process.
Do you handle both Adobe and Salesforce stacks together?
Frequently. Plenty of enterprises run Adobe for experience and analytics and Salesforce for CRM and service. We design the integration between them rather than pushing you to standardise on one vendor.
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