Embarking on Your Secure AI Journey: How Businesses Can Leverage AI Safely
Artificial intelligence (AI) is often hailed as the next frontier of innovation, transforming business operations and delivering unprecedented efficiencies. With capabilities doubling every 70 days, AI’s march forward has never been more relentless—or more exciting. Yet for many C-Suite execs, owners, and business technology managers, the real question isn’t whether to adopt AI but how to do so securely and responsibly.
We’re excited to announce our new partnership with Hatz.ai—a collaboration resulting in a Secure AI platform built for small to medium businesses and enterprises. Recently, our press releases on this partnership received national coverage by the Associated Press (AP News), San Francisco’s Kron 4 (Kron 4 coverage), and Portland’s Koin 6 (Koin 6 coverage). This spotlight reflects the growing demand for solutions that balance AI innovation with robust data protection.
What follows is a journey through the AI landscape—exploring benefits, risks, and best practices in adopting Business AI tools with Privacy and Security.
The AI Journey Begins: “AI Is Like Having Infinite Interns”
As Ethan Mollick, Associate Professor at Wharton’s Generative AI Lab, puts it:
“AI is like having infinite interns—fast, eager, tireless, but needing direction and boundaries.”
AI isn’t magic; it’s a tool. It delivers the best results only when you train it, guide it, and maintain control. For businesses that juggle rapid innovation alongside data governance, it’s crucial to remember that a lack of structure or oversight can be detrimental.
Doing Nothing Comes With Risk
When organizations delay or avoid AI adoption, they face serious pitfalls:
- Shadow AI Usage: Employees may use AI regardless of approval, creating unregulated data trails.
- Data Governance & IP Issues: Sensitive information could end up in external systems.
- User Access Control Weaknesses: Without centralized oversight, ensuring consistent security and usage policies is difficult.
- Unstandardized Methods: Different teams might adopt different AI tools, resulting in a fragmented approach.
- Data Security & Privacy Concerns: Free platforms, like public ChatGPT or other LLMs, may train on your data.
- AI Hallucinations: Without training, employees risk misusing AI outputs, sometimes accepting incorrect information.
Remember: If the product is free, you are the product. Free AI platforms often rely on user data to refine their models. That’s no better than sharing documents via personal Gmail or Dropbox for sensitive company data.
Considering AI’s exponential acceleration, “the best time to start learning AI was yesterday. The second best time is today.”
Public AI Platforms and Your Data
Heroic’s Secure AI Platform Powered by Hatz.ai and Your Data
New Challenges in Managed & Secure AI
Beyond data security alone, we’re now seeing two additional hurdles that underscore why organizations need a flexible and manageable AI environment.
Rapidly Evolving AI Models
AI models seem to be leapfrogging each other monthly—if not weekly—on various benchmarks. Some excel at writing, others at software coding, and yet others at math. This constant shuffling of which model is “best” makes it unwise to commit to a single product or ecosystem.
Moreover, it’s unclear which AI platforms will still exist in two or three years. Betting your entire operation on a single AI vendor risks obsolescence if that vendor ceases to innovate or, worse, shuts down.
Where Heroic’s Secure AI Platform Excels
Powered by Hatz.ai, our Secure AI solution supports multiple leading LLMs, including OpenAI, Anthropic, Google, Meta, DeepSeek, and X.ai. This setup lets you choose the best model for the task at hand (e.g., writing, coding, analytics) without vendor lock-in. It’s your insurance policy against the rapidly shifting AI landscape.
Comparison of LLMs Supported by Secure AI Powered by Hatz.ai
This is a snapshot of the popular LLMs that are available on the Hatz AI platform. Please note that the context window and max output token limits are approximate and not always accurate, depending on the type of request and other factors.
| Company | Model | Reasoning?Check out our “Reasoning Models” article | Vision | Input Tokens / Words*** | Output Tokens / Words | Knowledge Cutoff Date |
|---|---|---|---|---|---|---|
| OpenAI | GPT 3.5 Turbo | 16K / 12K | 4K / 3K | September 2021 | ||
| OpenAI | GPT 4 | 8K / 6K | 8K / 6K | December 2023 | ||
| OpenAI | GPT 4o | Yes | 128K / 96K | 4K / 3K | December 2023 | |
| OpenAI | o1 | Yes | 200K / 150K | 100K / 75K | December 2023 | |
| OpenAI | o3-mini | Yes | 200K / 150K | 100K / 75K | December 2023 | |
| OpenAI | GPT 4.5 Preview | Yes | 128K / 96K | 16K / 12K | December 2023 | |
| Anthropic | Claude 3 Sonnet | 200K / 150K | 4K / 3K | August 2023 | ||
| Anthropic | Claude 3 Haiku | 200K / 150K | 4K / 3K | August 2023 | ||
| Anthropic | Claude 3.5 Sonnet v2 | Yes | 200K / 150K | 8K / 6K | April 2024 | |
| Anthropic | Claude 3.7 Sonnet | Yes (hybrid) | Yes | 200K / 150K | 8K / 6K | October 2024 |
| xAI | Grok 2 | Yes | 132K / 97K | 132K / 97K | July 2024 | |
| xAI | Grok 2 Vision | Yes | Yes | 132K / 97K | 132K / 97K | July 2024 |
| Gemini 1.5 Flash | Yes | 1 Million / 750K | 8K / 6K | November 2023 | ||
| Gemini 1.5 Pro | Yes | 2 Million / 1.5 Million | 8K / 6K | November 2023 | ||
| Gemini 2.0 Flash | Yes | 1 Million / 750K | 8K / 6K | June 2024 | ||
| Gemini 2.0 Flash Lite | Yes | 1 Million / 750K | 8K / 6K | June 2024 | ||
| MistralAI | Mistral Large | 32K / 24K | 4K / 3K | October 2023 | ||
| MistralAI | Mistral 7B Instruct | |||||
| Mistral AI | Mistral 8x7B Instruct | |||||
| DeepSeek | DeepSeek R1 | Yes | Yes | 32K / 24K | 32K / 24K | July 2024 |
| Meta | Llama 3.2 1B Instruct | |||||
| Meta | Llama 3.2 11B Instruct | Yes | ||||
| Meta | Llama 3.2 70B Instruct | |||||
| Meta | Llama 3.2 8B Instruct |
**For the most up-to-date supported model information, please visit here.
Use Cases by Company
| OpenAI | Sentiment Analysis, Content Generation, Process Automation |
| Anthropic | RFP Responses, Content Generation, Coding |
| xAI | Reasoning |
| Analyzing large documents, Summarizing reports | |
| Mistral | Translating, Trained with non-English data |
| Meta | Customer Support, Small, short tasks |
| DeepSeek | Reasoning |
Lack of Robust Management for SMEs
Many publicly available LLMs are great for experimenting, but they often lack enterprise-grade management features. The exceptions are typically those fully baked into productivity suites, such as Microsoft’s CoPilot in Microsoft 365 or Google’s Gemini in Google Workspace. Yet even these revolve around the vendor’s closed ecosystem, limiting flexibility.
- Management Capabilities to Consider: Easy user onboarding/offboarding, single sign-on (SSO), data-sharing policies, and security settings.
- Enterprise Plans: Some providers, like OpenAI’s ChatGPT Enterprise, only offer robust admin controls if you purchase a minimum of 150 seats or buy a private sandbox environment—an expensive commitment for many SMEs.
By contrast, Heroic’s Secure AI platform is designed with SMEs and enterprises in mind—no minimum user thresholds or forced tie-ins to a single platform. You get flexibility and centralized administration in a single system.
Introducing Secure AI for Small Business: Powered by Hatz.ai
In this evolving landscape, our Secure AI solution offers:
- Multi-Model Support: Access to a variety of LLMs—pick the right AI for the right job.
- Private & Safe: Data remains under strict organizational control, never used for external model training.
- Compliance & Governance: Built with GDPR and HIPAA considerations, providing high confidence for regulated industries.
- Centralized Administration: Manage user access, data policies, and security settings from one intuitive dashboard.
While we’re thrilled about our partnership with Hatz.ai, we weren’t part of the models’ original development—we simply bring these robust capabilities to businesses seeking reliable, secure AI.
Your AI Journey: Crawl, Walk, Run
For many organizations, AI adoption can still be intimidating—leading to technology skepticism, job replacement fears, or worries about skill obsolescence. Our Secure AI platform supports the proven Crawl-Walk-Run approach:
Crawl (Universal)
- AI Use Cases: Simple, immediate tasks (email summaries, meeting note generation) that benefit a wide audience.
- Minimal Learning Curve: Perfect for cross-departmental adoption with limited training required.
Walk (Templated)
- AI Use Cases: Complex tasks (advanced analytics, partial RFP responses) that require moderate customization.
- Reusability: Once templates are set, they can be replicated across multiple teams.
Run (Tailored)
- AI Use Cases: Specialized, high-impact projects unique to specific business units (custom sales forecasting, sophisticated compliance checks).
- High ROI: Requires expert-level implementation but can deliver significant competitive advantages.
Practical Skills: 10 Hours to Proficiency
Learning to use AI effectively is like learning to ride a bike—a little wobbly at first, but it becomes second nature with practice. Expect to invest 10 hours of focused hands-on time. Our Secure AI platform speeds this learning curve with a comprehensive training portal:
- Basic AI Terminology & Concepts
- Understanding Different LLMs
- Prompt Engineering
- Building Automations & Advanced Tools
Within this timeframe, employees from finance to operations can learn how to leverage Business AI tools with Privacy and Security responsibly.
Standard LLM vs. Secure AI: A Vital Difference
(Image Placeholder: A standard LLM diagram that trains on user-provided data vs. a Secure AI platform that does not train on user data.)
Standard LLM
- Data Aggregation: Public models ingest data from countless users, mixing private and public domains.
- Open Training: Your proprietary prompts can become part of future training sets.
- Security Gaps: Minimal or no control over how data is stored or used.
Secure AI Platform
- Controlled Environment: Data stays behind enterprise-grade security systems.
- No External Training: Your confidential data never enriches external models.
- Management Features: Centralized user administration, detailed activity logs, and advanced security policies.
This difference underscores why organizations should adopt a platform specifically designed for secure, multi-model AI usage.
Overcoming Common Challenges and Fears
By addressing these concerns head-on, you’ll pave the way for a successful AI rollout:
- Technology Skepticism: Pilot projects with quick wins demonstrate tangible ROI.
- Job Replacement Fears: AI handles repetitive tasks, enabling employees to focus on strategic, higher-level work.
- Ethical & Data Privacy Concerns: A robust governance model, data encryption, and role-based access instill confidence.
- Skill Obsolescence: With adequate training, employees quickly become AI-savvy, turning apprehension into enthusiasm.
Conclusion: Embrace the AI Journey
From rapidly evolving AI models to gaps in public LLM management, the AI landscape is as challenging as it is exciting. But with the Crawl-Walk-Run methodology and a Secure AI platform that doesn’t lock you into a single vendor, you can confidently chart a course for sustainable AI adoption.
As Ethan Mollick reminds us, AI can be an infinite number of interns—but only if you provide clear guidance and boundaries. Our partnership with Hatz.ai offers precisely that balance, ensuring your organization remains both innovative and compliant in an era where “the best time to start with AI was yesterday, and the second best time is today.”
