Enterprise AgentsSalesforce
Agentforce implementation.
Governed at enterprise scale.
dotSolved.ai provides Agentforce implementation and Agentforce consulting for Sales, Service and Marketing, backed by 23 years of enterprise implementation work. We deploy Salesforce's native agents with the permissions, approval paths and logging an enterprise needs, and build the agents Salesforce doesn't offer yet.
Salesforce: native AI and dotSolved.ai agentsNative AI
What Salesforce Now Offers Natively
Salesforce has introduced Agentforce, a suite of autonomous AI agents. dotSolved.ai implements these at enterprise scale with governance, security, and change management built in.
- Agentforce, autonomous AI agents for Sales, Service, and Marketing
- Atlas Reasoning Engine, Salesforce's LLM reasoning layer powering Agentforce
- Agentforce Builder, low-code/no-code agent creation and customization
- Einstein AI across Sales Cloud, Service Cloud, and Marketing Cloud
dotSolved.ai Original
What dotSolved.ai Builds on Top
Agentforce covers broad sales, service, and marketing automation. But enterprises need agents tailored to their specific revenue and customer success gaps.
Revenue Intelligence Agent
The Problem
Revenue forecasting relies on rep self-reporting, pipeline snapshots, and quarterly corrections. Deal risk is identified too late. Cross-sell and upsell signals are buried in CRM data.
What the agent does
Continuous revenue intelligence: deal scoring, pipeline risk detection, cross-sell and upsell signal identification, and forecast accuracy tracking, so revenue leaders review the pipeline daily instead of discovering problems at quarter end.
Customer Health & Expansion Agent
The Problem
Customer health is measured by the last NPS score and the renewal date. Churn signals such as declining usage, support escalations and champion departures are visible only in hindsight.
What the agent does
Customer health scoring that combines product usage, support data, billing patterns and engagement signals, with expansion opportunities and churn risk flagged for the account team to act on.
Agentforce implementation checklist
What should an Agentforce implementation settle before go-live?
Five things: the job the agent owns, the data it may read, the actions it may take, the approval path for each action, and the log that proves what it did. The short version is below. The full checklist, with the Salesforce settings to review at each step, is in Agentforce Implementation Checklist.
Step 1
Scope
One job, one team, one metric you will track from day one. Not a promised number, a measured one.
Step 2
Data access
A dedicated integration user, permission sets, field-level security and sharing rules reviewed before the agent reads a record. Read-only first.
Step 3
Actions and approvals
Every write action the agent may take, listed with its approval path, its permission set and how to reverse it.
Step 4
Testing
A test set built from real conversations and cases, with acceptance criteria agreed before rollout, not after.
Step 5
Operations
A named owner, logging on the Salesforce side and the agent side, cost reporting and a review cadence.
Data access is the step most teams rush
An agent, like Claude through an MCP server, reads Salesforce as an integration user, so OAuth scopes, permission sets, field-level security and sharing rules decide what it can see. Salesforce MCP Server: Governed Access for Claude walks through that design, and the Salesforce AI analytics and MCP data access page covers how Nexatron applies it to analytics.
In practice
Use Cases
How do we get real-time pipeline risk visibility instead of quarterly reviews?
The Revenue Intelligence Agent scores deals continuously, detects pipeline risk patterns, and surfaces cross-sell signals, so revenue leaders work from daily intelligence instead of quarterly reviews.
How do we deploy Agentforce safely across Sales, Service, and Marketing?
dotSolved.ai runs the Agentforce implementation with enterprise governance: data access controls, approval workflows and escalation paths, built from 23 years of enterprise implementation experience.
Can we see customer churn risk earlier?
The Customer Health & Expansion Agent combines product usage, support data, billing patterns and engagement signals to flag churn risk and expansion opportunities for the account team.
How do we get cross-platform intelligence between Salesforce and our ERP?
Nexatron federates data across Salesforce, Oracle Fusion, NetSuite and data warehouses, giving you a single question-and-answer layer across all platforms, and exposes it to agents and to Claude through MCP.
Nexatron by dotSolved Inc
Evaluate Salesforce pipeline analytics with Nexatron
Use a defined pipeline question, an approved Salesforce reference and the intended user's permissions to evaluate the product workflow. Claude can be the interface through MCP.
Explore Salesforce analytics in NexatronEnterprise Agents for Other Platforms
FAQ
Agentforce implementation FAQ
What Salesforce AI capabilities does dotSolved.ai implement?
What does Agentforce consulting from dotSolved.ai include?
What original AI agents does dotSolved.ai build for Salesforce?
Can an agent use data outside Salesforce?
Do I still need dotSolved.ai if I already have Agentforce?
Scope your first Agentforce agent
Bring one job, the Salesforce objects it touches and the person who will own it. We will map the agent, its permissions and its approval path in the first conversation.