Agentforce & AI

AI in Salesforce that does not just impress, but takes pressure off

Many companies talk about AI. Far fewer test concrete use cases in their own CRM. Aviando helps you place Agentforce sensibly, prioritise the right use cases and develop solutions that genuinely support teams in everyday work.

Review an Agentforce use case View use cases

Agentforce · sales assistant in your CRM

I analysed your open leads. 3 match your target profile and were active on the website this week.

Summarise the top lead for me.

Müller GmbH · mechanical engineering. Quote open, last contact 6 days ago. Recommendation: follow up today.

Works on your Salesforce data

AI does not need hype. It needs a clear point of entry.

Agentforce and AI can move a lot in Salesforce when goal, data basis and processes fit together. Without that foundation you quickly end up with demos that look good but change little in daily work.

That is why we do not start with technology, but with your workflows. Where do teams lose time? Which tasks repeat constantly? Where is context, speed or quality missing?

From these answers a realistic point of entry emerges. Small enough to test quickly. Relevant enough to show impact.

In practice

Agents in action

Order Processing Agent at Bewital

Orders arrive by email, in every conceivable format. The agent reads the order data straight from the files and fields of a record, for example from a case created from an order email: PDF, Excel, DOCX, TXT and CSV, as Salesforce Files or as classic attachments. Every result gets a confidence score with a rationale, so the team sees which extraction is reliable and which needs a second look. It is started via a button on the page or from any flow. Every run is logged, and a dashboard shows key figures, errors and a review list for uncertain results.

Visit Capture Agent at MC Bauchemie

Visit reports are created on the go, often only days later at the desk. The agent records the report by voice directly in the browser, or as text when recording is not possible. Transcription runs in Salesforce by default via a flow action, optionally through an external model. From the transcript a prompt template generates a structured summary that appears as suggestions for visit reports, contacts, opportunities and tasks. Each suggestion is accepted, edited or discarded individually, limited to the objects and fields the admin has approved. Stored audio files are deleted automatically by a retention job.

Topics

Why Agentforce becomes relevant in the CRM

For many companies Salesforce is the central place for customer data, leads, opportunities, cases, campaigns and activities. That is exactly where tasks come up every day that AI can better prepare, structure or partly automate.

Agentforce can help in particular when recurring work ties up a lot of time, information is spread across several sources or users need to reach a well-founded next action faster.

What stays decisive: not every task is suitable straight away. Aviando helps you recognise sensible entry points and deliver them cleanly.

Approach

Our approach

The use case first, then the solution
Good AI use starts with a precise question. Together we define which problem should be solved, which user group is affected and how success is measured.
Review the data basis realistically
AI can only work with what is available, understandable and usable. That is why we look at data quality, permissions, object structure, process logic and existing integrations before a pilot starts.
Pilot Agentforce pragmatically
Instead of writing long concepts, we build a manageable test case. That quickly shows whether the approach works, which adjustments are needed and how high the actual value is.
Involve people deliberately
New assistance features change ways of working. Users have to understand what an agent can do, where the limits are and when human judgement remains important.
Make impact measurable
In the end it does not matter whether a solution looks modern. What matters is time saved, data quality, process speed, acceptance and better decisions.

Use cases

Typical use cases

Prepare sales conversations

Sales teams need a quick overview of accounts, contacts, open activities and next steps. Agentforce can summarise relevant information and make conversation preparation more efficient.

Qualify leads

Not every enquiry deserves the same attention. AI can structure existing data, provide hints and help set priorities in a more traceable way.

Speed up follow-ups

After conversations, meetings or service contacts there is often manual follow-up work. Templates, summaries and next actions can be prepared so users spend less time on routine tasks.

Take pressure off service

Many support questions are similar. A cleanly scoped use case can help answer known requests faster, provide suitable information or route complex cases on in a targeted way.

Make knowledge usable

Information often sits in articles, notes, documents or past cases. AI can make access easier when sources are clearly structured and permissions are defined cleanly.

Support management

Leaders do not need more data, but better context. Summaries, trends and hints help spot developments earlier and prepare decisions on a sounder basis.

Services

Our services for Agentforce & AI

AI readiness check

We check whether your Salesforce setup is ready for concrete AI applications. This includes data model, permissions, process quality, integrations, documentation and organisational prerequisites.

Use case workshop

Together we identify use cases with real potential. Each proposal is assessed by value, effort, data needs, risk and feasibility.

Agentforce pilot

A first pilot makes impact visible. We develop a clearly scoped use case, test it with relevant users and derive next steps from it.

Salesforce delivery

When a use case convinces, we support configuration, adjustment, integration and handover into operation. We pay attention to stability, traceability and later extensibility.

Enablement and governance

Teams need confidence in working with AI. We develop training, role logic, guardrails and simple rules so new solutions are used responsibly.

Optimisation after launch

After go-live the real learning phase begins. Adoption, feedback and results show where an agent should be improved, extended or limited.

Impact

What improves as a result

A sensible use of Agentforce does not take responsibility away from teams. It reduces friction.

Sales can prepare conversations better. Service responds faster to recurring requests. Marketing and management get more context from existing data. Admins and business units gain clarity about which AI applications really help.
The result is not an isolated experiment, but a practical step towards more efficient CRM processes.

Flow in the CRM

Enquiry or activity lands in the CRM

Agent gathers context from Salesforce

Summary and next step

Decision stays with the team

Honestly

When Agentforce is not yet the right starting point

Not every company should start with an AI agent right away. When data quality, processes or permissions are still unclear, it is worth taking a clean look at the CRM foundation first.

In such cases we start with structure: which information is relevant? Where do errors arise? Which workflows need simplifying? Only then comes the right automation.

That protects against unnecessary complexity and increases the chance that AI delivers real value later.

Sounds like an AI use that could genuinely help in Salesforce?

Thorsten Winkels, co-founder and managing director of Aviando, looks with you at your Salesforce setup, possible Agentforce use cases and realistic next steps. Together you clarify where AI can take pressure off in the short term and which foundation is needed for it.

Book a meeting with Thorsten View Salesforce services

Thorsten Winkels

Co-Founder & Managing Director

Implementation

AI Strategy

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