Deep specialization in large language models: RAG architectures, fine tuning, chatbot development, and production-grade deployment across industries.
Whenever possible, we suggest using existing open-source frameworks and technologies, having product quality and customer experience as our priorities.
We build agent ecosystems and integrations using the Model Context Protocol, enabling reliable, composable AI workflows that scale with your business.
End-to-end ownership of your AI initiatives: from architecture to deployment to monitoring, so your team can focus entirely on business outcomes.
Conversational AI and RAG-powered chatbots tailored to your business context and proprietary data.
Precision model fine tuning to align LLM behavior with your domain, tone, and compliance requirements.
Adversarial testing and semantic fencing to secure your AI models against prompt injection and contextual drift.
Agent architectures and tool integrations built on the Model Context Protocol for composable AI workflows.
End-to-end Retrieval-Augmented Generation pipelines: ingestion, chunking, embedding, retrieval, and evaluation.
Applied data science and AI product development that transforms raw data into intelligent, production-ready solutions.
Full-lifecycle AI development under a managed services model — staffing, architecture, delivery, and ongoing support.
Software development and testing practices augmented with AI: automated testing, intelligent code review, and accelerated delivery.
AI security layer that protects LLMs with semantic fencing. Validates prompts in real time, prevents prompt injection, and ensures strict contextual compliance. Achieves a 99.36% average block rate across industry-standard attack datasets.
Learn more →Security auditing library that runs automated adversarial attacks against AI systems — LLMs and semantic fences alike. Coordinates four red-teaming frameworks (Garak, PyRIT, Inspect AI, promptfoo) and produces reports in PDF, HTML, CSV and Markdown.
Learn more →Hybrid, high-dimensional similarity engine built for RAG from the ground up. Combines keyword and vector search to return exact results — not approximations — so LLMs can respond consistently. Indexes up to 99× faster and searches using a fraction of the memory of comparable engines.
Learn more →We analyze your requirements, understand your business context, and identify the best approach for your unique challenges.
We design a tailored solution combining the right technologies, methodologies, and team structure for your project.
Our expert team implements the solution with continuous quality practices, agile methods, and transparent communication.
We ensure seamless deployment, knowledge transfer, and ongoing support to maximize the value of your investment.
Every solution starts with the question: how can language models make this better? We bring deep LLM expertise — RAG, fine tuning, agents, and MCP — to every engagement.
We use powerful data science techniques and quality practices to help our clients solve exciting business problems and optimize their business or products — guaranteeing quality in every step.
We measure success by business outcomes: adoption, accuracy, cost reduction, and ROI — not just technical metrics. Our success is the value we create for your organization.
The TekDatum Team is my go-to partner for engagements requiring a thorough understanding and application of data science. They can quickly bring together diverse teams of experienced professionals to address the complexities and challenges of building highly scalable assets that increase business value and data intelligence.