AllAi Competitive Landscape
- Monica Pastor
Table of contents
Document Version Control |
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Sep 11, 2024 |
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Notes
This document offers a comparative analysis of the AllAi capabilities against those of our main competitors, aiming to provide end users with a comprehensive overview of all available features.
While numerous AI assistants exist, our analysis specifically targets those offering a "platform" approach. This means they provide a wide range of capabilities for various roles and use cases, rather than focusing solely on AI guidance for a specific scenario.
Our comparison includes Salesforce Einstein, considering not only the Einstein platform but also all Salesforce Einstein assistants, such as Sales, Service, Dev Assistant, and Agentforce.
It's important to note that the AI industry landscape is constantly evolving, new capabilities may emerge and this analysis is performed with current public data. If you have any insights or updates you'd like to share, please reach out to the innovation team.
Battlecard
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General Available
Not available
In progress or experimental
Category | Feature | AllAi | Salesforce Einstein | GitHub Copilot | GitLab Duo | AWS Q | Tabnine |
Chat Assistance | AI Chat assistance | AllAi Code, Chat, Chrome, Doc, Experts |
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One click prompts | AllAi Chrome |
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Salesforce awareness | AllAi Chat |
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Sources references | AllAi Chat |
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File upload | AllAi Chat and Experts |
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Eloquence selection | AllAi Chrome |
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Image generation | AllAi Chat |
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multi-visual responses |
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| QuickSight: responses with data previews and dashboards |
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Access to web | AllAi Chat, Chrome, |
| web search powered by Bing |
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Predefined Salesforce AI assistants | AllAi Experts |
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Predefined AI agents | for improving the task and providing solution suggestions | Sales, Service agent | Workspace |
| Agent for software development | AI chat agents personalized to codebase | |
Create your own AI agents |
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| Create “apps” using natural language |
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Enterprise Knowledge | Project awareness |
| Salesforce org awareness | Code repository awareness | Code repository awareness | Connectors for wikis, intranets, Atlassian, Gmail, SF, SP, SNOW, Slack, etc. | Integration with Atlassian Jira and Confluence |
Corporate guidelines awareness |
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Role awareness | AllAi Chrome, just for SFMC at the moment |
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Enterprise search | Backlog item |
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Coding | Code inline completion | AllAi Code |
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Code explanation | AllAi Code |
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Code generation | AllAi Code, Chat, Chrome |
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Code optimization/ refactoring | AllAi Code |
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Docstring generation | AllAi Code, DevOps |
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Unit test generation | AllAi Code |
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Codebase indexing for context enrichment | AllAi Code |
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| AI models can be fine-tuned to codebase | |
Teacher mode | AllAi Code |
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Project documentation | Search in codebase | AllAi Doc |
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Codebase documentation generation | AllAi Doc |
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Codebase health check | AllAi Doc |
| Through integration with third parties |
| Through integration with third parties | ||
Codebase diagrams creation | AllAi Doc |
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DevOps | Pull/Merge request summary | AllAi DevOps |
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Inline Pull/Merge request completion |
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Pull/Merge request auto approval |
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| Auto-generated merge requests |
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Suggest reviewers for each pull request |
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Unit tests check and update | AllAi DevOps. point out missing unit tests as well |
| Pull request diff analysis |
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Docstring check and update | AllAi DevOps |
| Pull request diff analysis |
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Check vulnerabilities | AllAi DevOps (PMD Checker) |
| Through integration with third parties |
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Release notes generation | AllAi DevOps |
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| Code review summary |
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Metadata permission summary | AllAi DevOps |
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Code rewriting/ suggest fixes | AllAi DevOps |
| Debugging and security remediation assistance |
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Root cause analysis |
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Task management | Ticket/Issue/Case comments summarization | AllAi Jira | Case summary |
| Discussion summary |
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Functional Test case generation | AllAi Jira |
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Text improvement for tickets and comments | AllAi Jira |
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Requirement description improvement |
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| Issue description |
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Task steps suggestions | AllAi Jira |
| GitHub workspace |
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User stories generation | AllAi Jira |
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Configuration/admin | Reference tracker for open-source code |
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Community Support |
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User documentation |
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User training | Trailhead |
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Access management |
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In-product Usage analytics |
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| Usage metrics |
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AI Impact dashboards |
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| Cycle times and deployment frequencies |
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SSO authentication |
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Content exclusions |
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Private data storage |
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| Self-Hosted Model Deployment |
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LLM Model selection |
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IP indemnification |
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Optional model finetuning | But bring your own fine-tuned model | Fine-tuned models coming soon as add on |
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Technologies supported |
| Limited to Apex (Salesforce) | Other Languages (C++, SQL, Java, JavaScript, PHP, Python, Ruby, TypeScript, etc.) | Other Languages (C++, SQL, Java, JavaScript, PHP, Python, etc.) | (Python, Java, JavaScript, TypeScript, C#, Rust, Go, Ruby, Scala, Kotlin, PHP, C, C++, Shell Scripting, SQL,) | Other (Python, Java, Node.js, etc.) |
Insights
Most AI tools are designed for a single specific function like coding or documenting, and often lack deep accuracy for a particular domain. In contrast, AllAi is built to cover a wide range of functions, and it focuses specifically on one domain: Salesforce.
