Activate AI Inside
Your Revenue Team
Squivr optimizes your investment in AI and Salesforce streamlining how revenue teams build strategies, foster relationships, personalize customer interactions, and predict future trends.
Adoption went up.
Trust didn't follow.
AI in revenue teams stopped being the experiment. Most sales organizations now use it in some form for prospecting, forecasting, or scoring. But an adoption curve and a trust curve are not the same curve. A rep who can't see why a recommendation was made tends to quietly ignore it, no matter how accurate the model behind it actually is.
That's the case for rule-based AI over black-box scoring. When a recommendation comes from a visible, editable if-then rule instead of an opaque model, your team can see exactly which inputs produced which output, trust it faster, and challenge it when their own context calls for it. Explainability isn't a nice-to-have for adoption, it's the mechanism adoption actually runs on.
Rule-based AI built for
Relationship Management
Squivr specializes in rule-based artificial intelligence a type of AI that uses human-made rules to process data and make decisions. These rules are written as "if-then" statements, where "if" represents a condition and "then" represents an action or conclusion.
At Squivr, we focus on Relationship Management and Account Planning to unleash your revenue team's competitive advantage leveraging AI where it creates the most impact.
Connect with Squivr →Leveraging artificial intelligence for enhancing relationship management has become a business necessity. At Squivr, we focus on Relationship Management and Account Planning to unleash the revenue team's competitive advantage. We optimize your investment in AI & Salesforce to streamline how revenue teams build strategies, foster relationships, personalize customer interactions, and predict future trends.
The AI tools Squivr
activates for your team
Squivr helps you activate and leverage Salesforce Einstein's full suite of AI capabilities configured for your specific revenue workflows.
Predictive Scoring
Rank every record by AI-driven likelihood to convert, expand, or churn. Focus your team's energy where it will have the most impact on revenue.
Workflow Automation
Automate routine tasks like data entry and scoring to allow your team to focus on more strategic, relationship-driven activities.
Personalization at Scale
Use AI insights to guide personalized customer interactions ensuring every touchpoint feels relevant, timely, and tailored to the individual.
How Squivr activates AI
inside your Salesforce org
A clear, repeatable process to go from raw Salesforce data to live AI-driven revenue intelligence without ripping out what's already working.
Define Your AI Objectives
Before diving into the technicalities, outline what you aim to achieve with AI in your relationship management strategy. Whether it's improving customer service, personalizing marketing campaigns, or increasing sales prediction accuracy having clear objectives guides the entire implementation process.
Collect and Clean Your Data
AI thrives on data. The accuracy and effectiveness of your AI predictions depend heavily on the quality and quantity of data you feed into the system. Squivr helps ensure your Salesforce data customer records, interaction logs, sales history is clean, up-to-date, and ready for AI analysis.
Leverage Your Platform
Squivr helps you activate AI in Salesforce. With objectives in place and data ready, we configure Einstein's features Prediction Builder, Next Best Action, and Language and Vision specifically for your revenue team's workflows and use cases.
Integrate and Automate Workflows
With AI models in place, the next step is integrating them into your daily workflows. Automate routine tasks like data entry and lead scoring so your team can focus on more strategic activities. Einstein's insights guide decision-making in real-time, ensuring a more personalized and efficient customer experience.
Monitor and Iterate
AI is not a set-it-and-forget-it solution. Continuous monitoring is crucial. We help you evaluate prediction accuracy, impact on customer satisfaction, and overall business outcomes using these insights to refine models and ensure your AI evolves with your business needs.
Stay Informed and Compliant
Keep abreast of the latest AI advancements and ethical guidelines. AI in CRM is a rapidly evolving field with new features regularly introduced. We ensure your use of AI complies with data protection regulations like GDPR and CCPA, respecting customer privacy and consent at every step.
AI applied across every
Salesforce object you work on
Squivr activates AI on the specific Salesforce objects your revenue team uses every day from standard records to complex custom and junction object relationships.
Account
Apply AI scoring, sentiment analysis, and next best action recommendations directly on Account records to prioritize your highest-value relationships.
Account Plan
Drive AI-informed account planning by surfacing whitespace signals, expansion indicators, and strategic recommendations tied to each plan.
Opportunity
Score every opportunity by close likelihood, flag deal risk early, and surface the next best action to keep each deal moving forward.
Standard Objects
Activate AI across Salesforce standard objects Contacts, Leads, Cases, and more without any custom development or data migration.
Custom Objects
Extend AI to any custom object your org uses whether it's a product, project, or industry-specific record with the same rule-based framework.
Junction Objects
Apply AI intelligence to many-to-many relationships via junction objects unlocking insights across complex data structures unique to your business.
Common questions
about Squivr AI
Is Squivr's AI generative AI or rule-based AI?
Squivr is built on rule-based AI: human-defined if-then logic that processes your Salesforce data and produces a clear, explainable action. We also help you activate Salesforce Einstein's predictive features where a statistical model is the better fit, but our default leans toward rule-based logic anywhere your team needs to see exactly why a recommendation was made.
Does any of my Salesforce data leave Salesforce?
No. Squivr configures AI capabilities natively inside your existing Salesforce org. There is no external data store, no separate AI platform, and no data pipeline outside of Salesforce for Squivr to operate.
Which Einstein features does Squivr configure?
Depending on your use case, we configure Prediction Builder, Next Best Action, and Einstein's Language and Vision features, mapped to the specific objects and workflows your revenue team already uses.
What's the difference between rule-based AI and predictive AI?
Rule-based AI follows explicit if-then logic you define and can always trace back. Predictive AI uses a statistical model trained on your historical data to estimate a likelihood. Both have a place. We help you decide which approach fits each use case, and lean rule-based wherever explainability matters most to adoption.
Do I need to clean my Salesforce data before activating AI?
Clean, current data makes any AI model more accurate, rule-based or predictive. As part of activation, we help assess your existing Account, Contact, and Opportunity data and flag the gaps worth closing before rules and predictions go live.
Ready to activate AI in Salesforce?
See how Squivr can optimize your AI and Salesforce investment and give your revenue team a real competitive advantage.
Squivr’s Product Alignment - AI
Squivr specializes in - Rule-based artificial intelligence (AI) is a type of AI that uses human-made rules to process data and make decisions. These rules are often written as "if-then" statements, where "if" represents a condition and "then" represents an action or conclusion.
“Leveraging artificial intelligence (AI) for enhancing relationship management (RM) has become a business necessity. At Squivr, we focus on Relationship Management and Account Planning to unleash the revenue team’s competitive advantage.
We optimize your investment in AI & Salesforce to streamline how revenue teams build strategies, foster relationships, personalize customer interactions, and predict future trends.”
JP Leggett
Activating AI with Relationship Management with Squivr in Salesforce:
-
Define Your AI Objectives
Before diving into the technicalities, outline what you aim to achieve with AI in your relationship management strategy. Whether it's improving customer service, personalizing marketing campaigns, or increasing sales predictions accuracy, having clear objectives will guide your AI implementation process.
-
Collect and Clean Your Data
AI thrives on data. The accuracy and effectiveness of your AI predictions depend heavily on the quality and quantity of the data you feed into the system. Ensure your Salesforce data is clean, up-to-date, and comprehensive. This includes customer data, interaction logs, sales history, and any other relevant information that can be analyzed by AI.
-
Leverage Your Platform
Squivr helps you active AI in Salesforce. With your objectives in place and data ready, start exploring Einstein's features
Einstein Prediction Builder: Create custom AI models to predict outcomes based on your Salesforce data.
Einstein Next Best Action: Automate recommendations for your team's next steps.
Einstein Language and Vision: Utilize natural language processing to analyze text data from emails, social media, and web chatter to gauge customer sentiment.
-
Integrate and Automate Workflows
With AI models and tools in place, the next step is to integrate them into your daily workflows. Automate routine tasks, like data entry or lead scoring, to allow your team to focus on more strategic activities. Use Einstein's insights to guide decision-making in real-time, ensuring a more personalized and efficient customer experience.
-
Monitor and Iterate
AI is not a set-it-and-forget-it solution. Continuous monitoring of your AI tools' performance is crucial. Evaluate the predictions' accuracy, the impact on customer satisfaction, and overall business outcomes. Use these insights to refine your models and strategies, ensuring your AI evolves with your business needs and market changes.
-
Stay Informed and Compliant
Lastly, keep abreast of the latest AI advancements and ethical guidelines. AI in CRM is a rapidly evolving field, with new features and capabilities regularly introduced. Additionally, ensure your use of AI complies with data protection regulations like GDPR or CCPA, respecting customer privacy and consent.