The world’s leading LLM training services provider

Accelerate your LLM reasoning and coding capabilities by generating high-quality, proprietary human data for supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and direct preference optimization (DPO).

Accelerate your LLM reasoning and coding

Join top foundational LLM companies who have trusted Turing

Get comprehensive LLM measurement, improvement, and enhancement

Turing uses a multi-point model measurement, improvement, and enhancement methodology. This methodology optimizes the way your LLM training team approaches coding, data analysis, multimodal reasoning and more.

LLM Model Training and Enhancement

Model improvement analysis and assessment

Combine inputs and ideas from your product owners and researchers with our coding, data, and multimodal reasoning analysis

Post-measurement prioritization and progression recommendation

Our LLM training team configures to your new or backlogged training tasks based on skill relevancy and performance

Continuous task optimization and talent reallocation

Easily shift resource allocation as your product needs evolve with strategic reuse of our high-performing training team

Hyperspecifc evaluation and testing data generation

Get high-quality data with human discernment as the performance benchmark for your evaluation and testing tasks

SFT process

Get high-quality data employing SFT for continuous model enhancements on your identification and data generation tasks

RLHF and DPO cycles

Get high-quality data employing RLHF for continuous model enhancements on your comparison and judgment tasks

Your on-demand team of LLM technical advisors

Our technical advisors have helped multiple foundational LLM clients find success through our proven experience and our LLM training and development services.
Jonathan Siddharth
CEO, Repeat AI Founder ML, NLP, Search Researcher
Vijay Kishnan
CTO, Repeat AI Founder ML, NLP, Search Researcher
David Wei
Head of R&D, PhD Computer Science Prior: VP at Meta
Onkar Dalal
Head of Data & ML, PhD Machine Learning Prior: Director, LinkedIn
Mahesh Joshi
Head of ML Ranking, PhD in ML, NLP
Kai Du
Head of Gen AI, Prior: ML Systems, Data Labeling Systems
The AI that built Turing

Our experience, your LLM efficiency

Over the last two years, Turing has helped many of the most famous foundational LLM companies enhance their reasoning, coding, and other high level cognitive capabilities.

Turbocharge your LLMs with our network of experienced software engineers, trainers, data scientists and other technologists.
We can generate custom proprietary data for your fine-tuning and other training needs.

Accelerate your LLM training with experience

Turing has helped the world’s leading LLM companies with code generation and reasoning training solutions, generating custom proprietary data, and  fine-tuning, adapting, and enhancing LLM training capabilities. Our deep expertise comes from over a year of experience on a variety of generative AI and LLM use cases, including:
Real-time data analysis

Revolutionizing GenAI models with real-time data analysis

Enable an AI model to fetch and analyze real-time data for improved accuracy, adaptability and personalized insights in dynamic decision-making processes.

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AI model reasoning capabilities

Enhancing LLM reasoning capabilities for precise code validation

Enhance the reasoning capabilities of an AI model to reduce code errors during validation—generating and testing corner cases for error-free code.

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AI code generation

Transforming AI code generation with iterative debugging

Using problem statements and brief instructions, an AI model can generate code, evaluate it, recognize mistakes, and attempt to fix them.

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Our high-quality data generation examples using SFT, RLHF, and DPO

  • Identifying the source code that introduces a specific bug, including syntax, runtime, semantic, and logical errors
  • Conversational datasets of developers discussing code/debugging to trace errors and understand thought processes
  • Exercises in explaining code, writing comments, performing code reviews, and translating code
  • Leetcode-style problem-solving with thought process explanations and the development of debugging skills
  • Writing unit test cases and creating multiple-choice questions for assessing code understanding
  • Development scenarios (like building apps) with the assistance of LLMs documented in multimodal data formats which include sharing screen data and speech data of developers explaining what they are doing
  • Tasks involving software installation, devops, database queries, and integrations across various cloud services
  • Analyzing and manipulating data in response to specific tasks, and producing structured output formats
  • Teaching the model when and how to retrieve external information
  • Using retrieval as a means to reduce errors in the model's output (hallucinations)
  • Interfacing with different software and tech areas
  • Engaging in open source projects to understand application, contribution, and improvement strategies
  • Creating and understanding datasets in various programming languages, enhancing multilingual coding capabilities

Using the model to solve and represent scientific problems such as those in physics, mathematics, and economics through Python code

  • Integration with external agents or selecting appropriate internal functions to yield the correct output
  • Sequencing calls and functions for logical problem-solving.
  • Tackling competitive coding and scientific problems that require invoking correct formulas/functions
  • Reducing hallucinations through structured data output and teaching the model to handle uncertainty in queries
  • Explanations involving diagrams or visuals alongside text
  • Flowcharts and logic diagrams for business understanding
  • Generating operational prototypes from conceptual designs
  • Competitively solving coding problems that contain geometric elements with visual aids
  • Speech data of verbal explanations as part of the multimodal data involving explanations of code, system design concepts, and other logic diagrams
  • Developing intermediate step explanations, particularly with code implementation, to enhance programmatic reasoning
  • Teaching the model to discern appropriate tool usage
  • Comparing model outputs on different tasks, supplying corrections as needed
  • Evaluations through benchmark datasets
  • Recording on-screen actions for training agents to perform end-to-end tasks
  • Dialogues that capture the exchange between developers, deepening the model's understanding of real-world programming scenarios

We provide your most scaleable LLM training solution ever

As the world’s first AI-powered tech services company, helping companies embrace cutting-edge technology is in Turing’s DNA. Our proprietary AI-powered developer sourcing, vetting, and matching platform assembles the right team of specialists to overcome your research, procurement, and operational challenges.

A global network of technical talent for your tasks

Deeply vetted and on-demand

Our global network of over 3 million on-demand trainers, labelers, and other specialists support your data generation, documentation, fine-tuning, RLHF, DPO and other tasks.

Fully managed and customized teams

Our teams are built to your specifications across preferred programming languages, roles, seniority levels, and more for a personalized fit.

Easily scalable and cost efficient

Our operating model rapidly scales with your development needs within weeks, while maintaining cost-efficiency to keep projects on-budget.

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