Guardrails

While ChatGPT/LLMs can generate text that appears human-like, they are prone to error. There is a risk of hallucination or making things up that are not true. To navigate this, we've established robust guardrails, custom-designed to manage these risks effectively. ThinkCol provides expertise in setting up these controls, ensuring your LLM operates within ethical boundaries and adheres to compliance standards. We assist with blocking prompt injection, hallucinations, out of context responses and develop monitoring systems that flag and address inappropriate outputs, securing both your data and your reputation.

Advanced RAG:

ThinkCol takes LLM capabilities a step further with our advanced Retrieval-Augmented Generation framework (RAG). An LLM can understand a corporate domain by providing it with the context via a vector database and then allowing the LLM to generate the answer based on the context, ensuring that generated answers are not just accurate but also highly relevant.

The RAG Process:
• Contextual Embedding: We embed corporate data into a vector database, creating a rich context layer for the LLM.
• Prompt Engineering: By crafting specific prompts, we guide the LLM to search for and utilize the most relevant answers from the database.
• Tailored Responses: The result is a highly accurate, context-aware response that perfectly aligns with your business needs.

Fine-tuning:

Every business is unique, and a one-size-fits-all approach doesn't work in the realm of AI. ThinkCol specializes in fine-tuning LLMs to meet the specific demands of your business. By customizing the open-source model with targeted datasets using techniques such as LoRA, we ensure that the AI solution you get is not just powerful but also perfectly aligned with your business objectives.