AI agents only work when the data is in order.
We implement Agentforce and Data Cloud on Salesforce for US and Latin American companies. First we unify and govern the data; then we build agents that resolve real service and sales cases, with a record of what the agent did and why.
Discovery Partners, in one sentence
Discovery Partners is a technology consulting firm specialized in SAP, Salesforce, IT staffing, AMS support and integrations, with its own teams in Colombia, Mexico, Peru, Costa Rica, Guatemala and the United States, plus additional regional or remote coverage across Latin America.
In Salesforce we are a partner with a verifiable AppExchange profile. In SAP we are an SAP Service Partner, which lets us connect the CRM to the ERP without a third party in between.
- ProductsAgentforce, Data Cloud, Sales Cloud, Service Cloud and Marketing Cloud
- Technical baseData unification, governance, integration and security
- IntegrationsSAP S/4HANA and ECC, in-house systems and third-party APIs
- Track recordMore than 100 combined SAP and Salesforce projects
What we build with Agentforce and Data Cloud
Order matters: most agent projects that fail do not fail because of the model, they fail because the data was scattered, duplicated or had no clear permissions.
Data unification
We consolidate customers, accounts and contacts scattered across CRM, ERP and in-house systems into a single profile.
- Ingestion from SAP, internal databases and APIs
- Identity resolution and deduplication
- A documented common data model
Governance and permissions
We define what data each agent can see and use, and keep a record of every action it takes.
- Profiles, permissions and role visibility
- Sensitive fields excluded from context
- Traceability of agent actions
Service agents
Agents that resolve frequent customer questions and escalate to a person when they should.
- Order and invoice status lookups
- Answers grounded in the customer's real data
- Escalation with full context
Sales agents
Support for the commercial team in meeting prep, opportunity follow-up and CRM hygiene.
- Account summary before each meeting
- Activity logging without manual work
- Alerts on stalled opportunities
SAP integration
We connect Salesforce to your ERP so the agent answers with real inventory, pricing and billing.
- Interfaces with SAP S/4HANA and ECC
- Customer and order synchronization
- Error monitoring and reprocessing
Measurement and tuning
We define what "the agent works" actually means and measure it, instead of assuming the AI is already solving things.
- Resolution rate without human intervention
- Escalated cases and why
- Iterative tuning of instructions and data
Readiness assessment before building
Before implementing an agent we check whether the data, the permissions and the processes can support it. If they cannot, that is the first project.
Data assessment
We review where customer data lives, how duplicated it is and what is missing to unify it.
- Inventory of sources and systems
- Master data quality and duplication
- Permission and security gaps
- Report with priorities
Data Cloud
We build the foundation: ingestion, identity resolution, data model and governance.
- Connection of internal and external sources
- Unified customer profile
- Segments and activation
- Documented access rules
Agentforce
We design and publish the agents on that foundation, with scoped and measurable use cases.
- Definition of topics and actions
- Testing with real cases before go-live
- Escalation to people where appropriate
- Outcome measurement and tuning
From idea to an agent in production
Use case
We pick a scoped case with real volume and a measurable outcome, instead of trying to automate everything at once.
Data and permissions
We prepare the sources, unify the customer profile and define what the agent is allowed to see.
Build and test
We configure topics, actions and integrations, and test with real conversations before publishing.
Production and improvement
We go live with monitoring, measure resolution and escalation, and tune continuously.
Regional coverage in English and Spanish
Six primary markets with our own teams, plus regional or remote coverage across the rest of Latin America.
These six are our primary markets, with offices in Medellín and Mexico City. We also serve Panama, the Dominican Republic, El Salvador, Honduras, Nicaragua and other Latin American markets regionally or remotely, depending on availability and project scope.
Common questions about Agentforce and Data Cloud
Do we need Data Cloud to use Agentforce?
Not in every case, but in most of the ones worth doing. An agent answers with the data it can reach: if that data is scattered or duplicated, the agent answers badly. Data Cloud is what unifies the context.
How do we stop the agent from saying wrong things?
By scoping it. We define concrete topics and actions, ground the agent in verifiable data from your CRM and ERP, and set the conditions under which it must escalate to a person instead of improvising.
What about our customers' sensitive data?
We define upfront which fields enter the agent's context and which stay out, and apply Salesforce profile permissions. Every agent action is logged.
Can it connect to our SAP?
Yes, and that is usually what makes the agent useful: answering with real inventory, pricing, orders or billing status. We are an SAP Service Partner as well as a Salesforce partner, so one team handles the integration.
How long until a first agent is in production?
It depends mostly on the state of your data, not on configuring the agent. That is why we start with the assessment: with that result we can give a realistic timeline instead of a catalog one.
What if we are not on Salesforce yet?
Then the starting point is a Sales Cloud or Service Cloud implementation. We can do both: implement the CRM and leave the data foundation ready to add agents later.
Other areas where we can help
Content reviewed and updated in August 2026.
Can your data support an AI agent?
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