"A logical conclusion or consequence of facts." - Wiktionary.
Transform your operational data into actionable intelligence and gain AI insights to streamline HR, fortify data security, or unveil game-changing business intelligence—unleash AI on your data with SEQUITUR.
Enabling AI on enterprise data converts proprietary assets—customer records, sales metrics, and domain knowledge—into a significant competitive advantage. Grounded AI provides AI insights that are far more accurate and relevant than public-data models alone, uncovering patterns, accelerating decisions, personalizing experiences, optimizing operations, and reducing human review costs. Companies that let their rich internal data remain siloed miss out on substantial value, while those that leverage AI against this data enhance their business intelligence and quickly gain an edge in performance, efficiency, and enduring advantage, all while ensuring data security.
Leverage advanced AI insights through secure AI inference directly on your private corporate, sales, marketing, and product data, ensuring data security by keeping everything within your environment and avoiding the transmission of sensitive information to external servers. Analyze patterns, trends, customer behaviors, pipeline dynamics, and campaign performance with robust business intelligence.
Apply powerful AI insights securely on your private HR, employee, and workforce data, leveraging business intelligence to analyze performance metrics, engagement surveys, turnover patterns, recruitment pipelines, compensation structures, and talent development records while ensuring data security without ever leaving your environment.
Apply advanced AI insights securely to your private security logs, network traffic metadata, identity and access events, vulnerability scan results, incident tickets, and threat intelligence feeds—processing everything entirely within your controlled environment to enhance your business intelligence without exposing sensitive data externally.
AI insights that lack access to your actual enterprise data rely solely on their general training, which can lead to hallucinations or confidently incorrect answers when addressing company-specific facts, proprietary processes, internal metrics, customer details, or recent/unpublished events. Without grounding in real data, the model fills gaps with plausible-sounding but fabricated information, resulting in errors, misguided decisions, compliance risks, and undermined trust in business intelligence and data security.
Using public LLMs with private enterprise data poses significant data security risks, as your sensitive information—such as customer records, IP, financials, and trade secrets—is transmitted to third-party servers. This data can be logged, stored, or utilized for model training, either intentionally or through data leaks, potentially accessible by the provider’s staff. Such practices create irreversible exposure risks, including compliance violations (GDPR, HIPAA, DLP rules), competitive leakage, and IP theft. Furthermore, the threat of future model poisoning or inversion attacks that could reconstruct your data adds to the vulnerability. Once your data is uploaded, you lose control forever, jeopardizing your business intelligence and the insights derived from your AI operations.
The widespread, uncontrolled use of AI chatbots by employees poses significant risks to data security and business intelligence. It can result in inconsistent outputs, frequent hallucinations regarding company-specific facts, and the accidental leakage of sensitive data to public models. Additionally, non-compliant responses may violate regulations or brand standards, leading to duplicated efforts as employees reinvent answers. This scattered tribal knowledge becomes impossible to govern, audit, or improve, effectively turning a powerful tool into a source of hidden errors, legal exposure, and a loss of institutional control.
SEQUITUR provides reusable, shareable expert prompts for dashboards, reports, and workflows that unleash AI insights on enterprise data by standardizing high-quality, grounded queries. This approach eliminates hallucinations, inconsistent answers, and errors, thereby enhancing data security. A governed prompt library scales vetted expertise organization-wide, ensures compliance and consistency, cuts redundant engineering, accelerates adoption, and improves continuously—transforming chaotic AI use into reliable, enterprise-grade business intelligence.
AI insights that lack access to your actual enterprise data rely solely on their general training, which can lead to hallucinations or confidently incorrect answers when addressing company-specific facts, proprietary processes, internal metrics, customer details, or recent/unpublished events. Without grounding in real data, the model fills gaps with plausible-sounding but fabricated information, resulting in errors, misguided decisions, compliance risks, and undermined trust in business intelligence and data security.
Using public LLMs with private enterprise data poses significant data security risks, as your sensitive information—such as customer records, IP, financials, and trade secrets—is transmitted to third-party servers. This data can be logged, stored, or utilized for model training, either intentionally or through data leaks, potentially accessible by the provider’s staff. Such practices create irreversible exposure risks, including compliance violations (GDPR, HIPAA, DLP rules), competitive leakage, and IP theft. Furthermore, the threat of future model poisoning or inversion attacks that could reconstruct your data adds to the vulnerability. Once your data is uploaded, you lose control forever, jeopardizing your business intelligence and the insights derived from your AI operations.
The widespread, uncontrolled use of AI chatbots by employees poses significant risks to data security and business intelligence. It can result in inconsistent outputs, frequent hallucinations regarding company-specific facts, and the accidental leakage of sensitive data to public models. Additionally, non-compliant responses may violate regulations or brand standards, leading to duplicated efforts as employees reinvent answers. This scattered tribal knowledge becomes impossible to govern, audit, or improve, effectively turning a powerful tool into a source of hidden errors, legal exposure, and a loss of institutional control.
SEQUITUR provides reusable, shareable expert prompts for dashboards, reports, and workflows that unleash AI insights on enterprise data by standardizing high-quality, grounded queries. This approach eliminates hallucinations, inconsistent answers, and errors, thereby enhancing data security. A governed prompt library scales vetted expertise organization-wide, ensures compliance and consistency, cuts redundant engineering, accelerates adoption, and improves continuously—transforming chaotic AI use into reliable, enterprise-grade business intelligence.
Pay only based on how much you use. Start with $10 usage credit. Buy usage credits using Credit Card or Cash App. Usage is counted from input and output tokens. $50 per million total tokens.
Annual contract value payable upon delivery and sign-off of solution. Typically, these solutions are provided by our Embedded Engineer within a month or less.
Let's meet: info@2ndthoughts.ai (469) 587-9991
* All prices are in USD
Please reach us at dev@2ndthoughts.ai if you cannot find an answer to your question.
SEQUITUR supports directly Importing your data from Comma Separated Values (CSV) files, Excel spreadsheet files, or MySQL dump files. We can also connect directly to your MySQL database or Snowflake data warehouse. Your data will be presented as a Dataset that you may select and ask questions, create dashboards and analysis reports.
Additionally, an ETL script can be deployed to create or update the dataset via downloads or API calls.
In an Enterprise environment, SEQUITUR can be deployed directly into your Amazon AWS Virtual Private Cloud and directly connect to your private database.
Your imported data is never shared nor accessible by users you do not allow access to. For further security, we can always deploy into your Virtual Private Cloud (VPC) environment in AWS.
Additionally, your data is never directly exposed to the underlying Large Language Model (LLM), neither in training, nor in inference. You may also use your own Enterprise LLM API keys. We currently support Grok and OpenAI.
Yes, please contact demo@2ndthoughts.ai through an email request for your situation and we can help you achieve your demo goals.
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