SherlockAI

Sherlock (https://sherlockai.pro/) — a platform for AI assistants that understand your business and respond to queries in seconds. It combines search and smart chat, instantly finding the required information in the knowledge base with source attribution. Thanks to flexible indexing and multilingual support, Sherlock accelerates processes, boosts productivity, and helps manage large volumes of information.

What problems does Sherlock solve? Manufacturing companies face several daily challenges that lead to inefficiencies. One of the key difficulties is the fragmentation of data stored across different systems, requiring significant time to locate the necessary information. Additional complications arise from human errors, which can result in costly failures and delays.

Moreover, training new employees often demands considerable time and resources, as newcomers need to familiarize themselves with extensive documentation and instructions. Another significant issue is the lengthy and labor-intensive ISO compliance audits, which take weeks of manual work and increase the risk of non-compliance. Sherlock effectively addresses all these challenges, ensuring speed, accuracy, and process optimization in production environments.

Key advantages of Sherlock AI:

Time savings: Instant search and chat accelerate access to data, reducing manual efforts.
Accuracy: Every response is accompanied by a source reference, ensuring reliability.
Multilingual support: Works with documents in various languages, simplifying collaboration for global teams.
Integration with corporate systems: Sherlock can connect to CRM, ERP, and BI systems for advanced analysis and data management.
User-friendly interface: Intuitive search and chat functionalities that require no specialized training.
Result: Tasks are completed up to 70% faster, with a +40% increase in productivity.

Sherlock leverages Retrieval-Augmented Generation (RAG) technology, which combines AI-based text generation with precise data retrieval from a preloaded knowledge base. Unlike traditional solutions, Sherlock delivers instant and accurate answers rather than just keyword-based search results. Its versatility enables the tool to be used across various industries, from manufacturing and education to IT companies. A key advantage of Sherlock is its ability to integrate with existing systems and adapt to client needs.

Furthermore, Sherlock supports all popular LLM models, including:

GPT by OpenAI (GPT-3.5, GPT-4, GPT-4 Turbo, GPT-4o), Mistral, Groq, Gemini, LLaMA by Meta, Claude by Anthropic.
Sherlock also supports integration with CRM, ERP, BI, and other document management systems. The only requirement is that the platforms in use must support API connectivity.

Working solution

Real-world cases of Sherlock implementation by companies:

Equipment diagnostics
On one occasion, operators in a production facility spent two hours searching for a repair manual. With Sherlock, this process took seconds.

Onboarding new employees
When a new employee starts at a factory, they often require a mentor, which costs time and money. Sherlock enables newcomers to find answers independently, saving company resources.

ISO compliance
Preparing for certification typically involves weeks of manual work. Sherlock uploads all regulations, compares them to ISO requirements, and immediately provides recommendations. This accelerates the process and reduces risks.

Specific industries:

Legal departments: Reduces the time spent searching for regulatory documents by 60%, improving legal support through chat functionality.
HR departments: A knowledge base chat enables quick answers to employee questions about internal policies and labor laws.
Consulting on educational institution selection: Search and chat functions allow consultants to instantly access necessary data about educational institutions and programs.

2024 Results:

June 2024
Initiation of platform development.

November 2024
Launch of SherlockAI, designed with scalability in mind.

Initial achievements:

First client contract: $3,007
Ongoing negotiations with potential clients for contracts ranging from $10,000 to $24,000

Economic impact:
Sherlock delivers substantial time savings by reducing the effort required to search for information and perform routine tasks. This helps companies streamline processes, lowering labor costs and minimizing errors caused by human factors. For example, using Sherlock in manufacturing reduces the time spent searching for documentation from hours to seconds, leading to cost savings of 20–30%, depending on the company’s scale.

Social and environmental impact:
Sherlock reduces employee stress associated with excessive information overload and simplifies the onboarding process for new hires. In the long term, this increases employee satisfaction and decreases turnover rates. Additionally, process automation with Sherlock minimizes the reliance on paper documentation, contributing to environmental sustainability.

Why now?
The AI market is projected to grow from $190 billion to $1 trillion by 2030 (PwC).

With advancements in GPT and AI technologies, it’s clear that the market is ready for such solutions. Companies are actively seeking ways to accelerate their processes, and Sherlock is the tool that delivers results starting from the very first week of implementation.

Aim: to achieve Monthly Recurring Revenue (MRR) of $100,000.

Investment Allocation:

50%: Development and platform improvement
30%: Marketing and expansion into new markets
20%: Operational expenses
Scaling Opportunities:

Expanding platform functionality to support additional languages and regions
Integrating with popular CRM systems and knowledge management platforms
Increasing data processing capacity and enhancing performance for large enterprises

1. Alibek Polatov

Over 11 years of experience in software development and digital marketing.
Co-founder of a successful software development company.
Master’s degree in Applied Mathematics and Informatics, Moscow State University (MSU).
2. Magzhan Ikram

Over 9 years of experience in building technology companies.
Co-founder of a successful high-tech company in Singapore.
Master’s degree in Applied Mathematics and Informatics, Moscow State University (MSU).
3. Dilshat Uteshev

Over 10 years of experience in developing and implementing AI technologies.
Professional experience at JPMorgan Chase, GSK, and Accenture.
Led the creation of products based on Generative AI.
Master’s degree in Applied Mathematics and Informatics, Moscow State University (MSU), and MBA from Strathclyde Business School (UK).