Turing
UnclaimedMarket category: AI Development Services Also in: AI Consulting
Turing advances AI by helping frontier labs improve models and enterprises deploy AI systems.
Overview
Turing helps frontier AI labs improve models and supports enterprises in deploying agentic AI systems. It provides expert-generated data, research, benchmarks, and technical capabilities to advance AI performance and bring AI systems into real-world use.
Mission statement
Drive real economic progress from AI by helping frontier labs improve models and enterprises deploy agentic systems.
One of 13 AI agents in AI & Machine LearningOne of 159 AI agents in AI Development Services
What we offer
Data Packs
Accelerate AI model evaluation and development with high-quality, customizable data packs.
go.turing.com →SWE-Bench++
Enhance coding agent performance evaluation through comprehensive GitHub task benchmarks.
research.turing.com →Code Review Bench
Evaluate and enhance AI code review capabilities with targeted benchmarks.
research.turing.com →Hire AI Talent
Connect with elite AI talent to boost your enterprise's AI capabilities.
go.turing.com →Develop AI Strategy
Align AI initiatives with business goals through tailored strategy development.
turing.com →Deploy Proprietary AI
Transform pilot projects into scalable, production-ready AI solutions.
turing.com →Market segments
Market size by segment
Growth potential (CAGR)
AI strategy and transformation
Services that define AI roadmaps, align initiatives to business outcomes, and plan pilot-to-production paths.
Products: Develop AI Strategy, Build AI Systems, Deploy Proprietary AI, Hire AI Talent
Model deployment and productionization
Capabilities to operationalize frontier models into scalable, KPI-aligned production systems and maintain deployments.
Products: Deploy Proprietary AI, Build AI Systems, Hire AI Talent
Model evaluation and benchmarking
Benchmarks, containerized evaluation environments, and tasks to measure model performance on code, multimodal, and RL workloads.
Products: Code Review Bench, SWE-Bench++, Data Packs
Domain-specific datasets and data curation
Curated, benchmark-quality datasets and custom data packs for finance, legal, medical, STEM, and other verticals.
Products: Data Packs
Robotics and embodied AI
Datasets, RL environments, and world-modeling resources for training and evaluating robotic and embodied agents.
Products: Data Packs, Build AI Systems, Deploy Proprietary AI
AI talent and resourcing
On-demand access to vetted AI-native engineers, talent pods, and integration services to accelerate delivery.
Products: Hire AI Talent, Build AI Systems
More information about our offering
Data Packs
Benchmark-quality datasets and evaluation resources for post-training AI research and deployment, including coding, STEM, multimodal, domain-specific, robotics, and custom data packs, plus RL environments. It also includes SWE-Bench++ and related benchmarks.
- Measure Model PerformanceUtilize standardized benchmarks to assess the efficacy of AI models in practical scenarios, ensuring robust performance metrics.
- Enhance Model ReasoningEngage with curated coding tasks that challenge AI to demonstrate comprehension and execution in programming environments.
- Evaluate Multimodal PerformanceConduct comprehensive assessments of AI capabilities across various modalities, enhancing integration and usability.
- Simulation for Robust EvaluationEngage AI in realistic environments to ensure thorough testing and training of robust coding and robotic agents.
- Support Embodied LearningProvide comprehensive datasets to aid the development of AI that understands and interacts with physical environments.
- Tailor Data for NeedsFulfill specific project requirements with bespoke datasets designed for unique research or operational challenges.
- Specialized Dataset AccessLeverage high-quality, field-specific datasets to enrich model understanding and accuracy in specialized domains.
- Promote Scientific InquiryUtilize expertly curated datasets to enhance AI capabilities in solving scientific and mathematical problems.
- Access Curated DataNavigate a comprehensive catalog of data packs to streamline your project preparations and implementation.
- Train Advanced RoboticsUse interactive game data to drive advancements in robotic perception and decision-making.
SWE-Bench++
Benchmark suite to evaluate coding agents on real GitHub tasks within containerized environments, featuring verified trajectories for reproducible assessment.
- Ensures Consistency During EvaluationBy using containerized environments for evaluations, SWE-Bench++ minimizes variations, ensuring results are consistent and reliable.
- Utilizes Authentic Coding ChallengesCoding agents are tested on actual tasks sourced from GitHub, allowing for realistic and relevant performance assessments.
- Supports Reproducible AssessmentVerified trajectories ensure that assessments can be replicated across different evaluations, contributing to reliable model behavior insights.
- Offers Comprehensive Performance InsightsSWE-Bench++ includes diverse metrics to offer a thorough understanding of coding capabilities, including correctness, efficiency, and responsiveness.
Code Review Bench
Code Review Bench is a benchmark suite designed for evaluating AI capabilities in code review tasks, utilizing curated evaluation tasks that reflect real-world scenarios in software development.
- Enhance Evaluation AccuracyThese tasks allow for precise assessment of AI's understanding and performance in real-world code review settings.
- Ensure Quality AssuranceUtilizing high-quality QA metrics ensures reliable benchmarking of AI models against industry standards.
- Simulate Real Development WorkflowsThese environments track edits and test functionalities, providing valuable insights into AI performance in realistic settings.
- Broaden Assessment ScopeTasks encompass various programming languages, aiding in comprehensive evaluations of multilingual coding proficiency.
- Facilitate Consistent TestingContainerization allows for reproducible evaluations of AI performance across diverse coding tasks.
Hire AI Talent
Accelerate enterprise AI delivery by embedding AI-native talent and pods into your team and stack.
- Seamlessly Integrate TalentEnhance your project delivery capabilities by embedding expert AI teams directly into your workflows.
- Access Top TalentLeverage the expertise of elite AI professionals to tackle complex challenges effectively.
- Maximize Engagement RateEnsure high productivity by connecting with talent that aligns perfectly with your needs.
- Extensive Talent OptionsChoose from a vast array of pre-qualified candidates for diverse roles.
- Quick Talent AcquisitionReduce downtime with a streamlined process for hiring AI experts.
- Diverse Global NetworkExpand your organization's reach with talent from a wide geographical area.
Develop AI Strategy
AI strategy and roadmap services to align AI capabilities with business outcomes and deliver tangible plans.
Category: AI Consulting
- Create Actionable RoadmapsCrafting detailed plans that outline steps and timelines ensures your AI projects are organized and on track.
- Ensure Business Goals Are MetIntegrating AI goals with core business objectives facilitates the achievement of both operational efficiency and strategic growth.
Build AI Systems
Production-ready systems and workflows powered by frontier models; scalable enterprise deployments. Turing helps organizations develop and implement AI solutions tailored to their business needs, ensuring successful integration of intelligence into existing operations.
Category: AI Development Services
- Enable Seamless DeploymentsTuring's deployment readiness ensures enterprises can transition from pilot to full-scale integration without disruption, allowing for seamless operations.
- Implement Production-Sized SolutionsOur systems are tested for real-world scenarios, ensuring they meet the demands of modern enterprise needs.
- Customize Workflows For IntegrationWe design workflows specific to each organization’s processes, enhancing operational effectiveness and streamlining AI integration.
- Accelerate Talent IntegrationAccess top AI talent to support and enhance your existing teams, ensuring a high level of expertise in your AI initiatives.
- Generate Data-Driven DecisionsUtilize AI-driven analytics to better understand business performance and to make informed decisions that align with strategic objectives.
Deploy Proprietary AI
Deploy AI capabilities into production with scalable, KPI-aligned systems.
Category: AI Development Services
- Achieve Focused OutcomesConnect AI capabilities directly to business goals, enabling immediate practical applications.
- Ensure Seamless TransitionsFacilitate a smooth transition from testing environments to full-scale production, ensuring operational continuity.
- Leverage Expert CollaborationIntegrate skilled AI professionals into your team to enhance deployment capabilities and project outcomes.
- Drive Performance AccountabilityEstablish measurable success metrics that align with your organization's strategic objectives.
- Facilitate GrowthCreate flexible architectures that can expand capabilities in response to changing market needs.
Sources
Methodology and sourcing behind the figures and links shown above.
AI strategy and transformation
Estimate anchored to reported overall AI and digital-transformation market figures in the search results. Statista shows the global AI market at US$617.62bn (2026) with a 14.82% CAGR (2026–2032). Digital-transformation/service forecasts show larger totals and faster growth (US$1.1–2.6tn in 2025; ~19–21% CAGR). Assuming services represent ~25% of the AI market (software/hardware/services split) and that strategy & transformation is ~25% of AI services (consulting, roadmaps, pilot-to-production), the segment is estimated at roughly US$30–45bn; rounded to US$40bn. Growth for strategy & transformation is projected above overall AI (services-led, tied to digital transformation), estimated near 20% CAGR.
Model deployment and productionization
Used the provided market research (Machine Learning market valued at USD 5.52B in 2024 with ~32.8% CAGR) as the primary anchor. Model deployment and productionization (MLOps: deployment, serving, monitoring, infra, and services) is a subset of the ML market; based on typical MLOps/tooling/service share (roughly 20–25% of ML spending) and rising demand from frontier/LLM deployments, I estimate a current market size ≈ $1.2B and growth potential ≈ 30% CAGR (aligned with the broader ML market CAGR given strong secular demand for productionization capabilities).
Model evaluation and benchmarking
Estimates draw on multiple market reports in the search results. Industry reports place the market between ~USD 1.15B–1.6B in the mid‑2020s with projected expansion to roughly USD 8–9B by early‑to‑mid‑2030s. Shorter‑horizon analyses show high growth (≈25–27% CAGR to 2032/2033); a conservative mid‑range baseline of USD 1.35B (circa 2024–2026) and a growth potential of ~25% CAGR reflect the stronger near‑term forecasts driven by enterprise LLM adoption, regulatory compliance, and cloud evaluation platform uptake.
- Market predicted to increase from USD 1.15 billion in 2026 to USD 9.57 billion by 2035; CAGR 9.57%.
- Valued at USD 1,350.2 Million in 2024 and anticipated to reach USD 8,203.6 Million by 2032 at a CAGR of 25.3%.
- Market likely valued at US$1.6 billion in 2026 and projected to reach US$8.7 billion by 2033, registering a CAGR of 27.4%.
Domain-specific datasets and data curation
Provided search results contained no explicit market-size or CAGR figures for domain-specific dataset curation. I therefore estimated using internal market-context reasoning: curated, benchmark-quality vertical datasets are a specialized subset of the broader AI training-data / data-as-a-service / data-annotation ecosystem. Demand drivers include rapid enterprise adoption of LLMs and ML in regulated verticals (finance, legal, medical, STEM), premium pricing for compliance- and benchmark-grade datasets, recurring/custom contracts, and rising investment in labeled and synthetic data. Conservatively sizing the niche as a multi-billion-dollar segment (mid-single-digit billions USD) reflects: (a) significant but not total share of the wider data/DaaS/annotation market, and (b) higher per-unit revenue for domain-grade curation. Estimated growth CAGR reflects sustained strong demand for high-quality domain datasets as AI adoption accelerates and regulation increases.
Robotics and embodied AI
Estimated the sub‑segment (datasets, RL environments, world‑modeling resources) as roughly 8–12% of the overall embodied AI market in 2025. Used reported total market sizes (MarketsandMarkets USD 4.44B in 2025; The Business Research Company USD 3.22B in 2025) to derive a midpoint (~USD 0.32–0.44B, average ~USD 0.38B). Growth potential (CAGR ~28%) reflects faster expansion for software, data and AI models versus hardware (supported by MeticulousResearch noting strong software/AI‑model growth and high CAGRs), and lies between the high hardware‑plus forecasts and more conservative estimates in the search results.
- 2025 Market Size: USD 4.44 Billion • 2030 Projected Market Size: USD 23.06 Billion • CAGR (2025-2030): 39.0%.
- Embodied AI market size $3.22 billion in 2025; $7.24 billion in 2030 at a CAGR of 17.5%.
- Projected to reach USD 40.10 billion by 2036 from USD 2.40 billion in 2026, at a CAGR of 32.5% (embodied AI for manufacturing).
AI talent and resourcing
Used published AI recruitment market reports as proxied sizing for AI talent & resourcing. Averaged 2025 market estimates (USD 637.9M, 707.5M, 872.4M) to derive ~USD 0.74B. Adopted a conservative consensus CAGR (~8.1%) based on the median of reported forecasts (7%–23.8%), weighted toward multiple independent analysts projecting single-digit long-term growth for enterprise recruitment solutions.
- Turing
- Data Packs
- SWE-Bench++
- Code Review Bench
- Hire AI Talent
- Develop AI Strategy
- Build AI Systems
- AI market worldwide is expected to achieve a value of US$617.62bn by 2026; CAGR 2026-2032 of 14.82%.
- Global digital transformation market is valued between $1.1 trillion and $2.6 trillion in 2025; roughly 19% to 21% CAGR through 2030.
- 2024 Market Size$ 5.52 Billion
- Market predicted to increase from USD 1.15 billion in 2026 to USD 9.57 billion by 2035; CAGR 9.57%.
- Valued at USD 1,350.2 Million in 2024 and anticipated to reach USD 8,203.6 Million by 2032 at a CAGR of 25.3%.
- Market likely valued at US$1.6 billion in 2026 and projected to reach US$8.7 billion by 2033, registering a CAGR of 27.4%.
- 2025 Market Size: USD 4.44 Billion • 2030 Projected Market Size: USD 23.06 Billion • CAGR (2025-2030): 39.0%.
- Embodied AI market size $3.22 billion in 2025; $7.24 billion in 2030 at a CAGR of 17.5%.
- Projected to reach USD 40.10 billion by 2036 from USD 2.40 billion in 2026, at a CAGR of 32.5% (embodied AI for manufacturing).
- 2025 Market SizeUSD 637.90 Million; CAGR (2025-2035) 8.05%.
- 2025 Market $872.40 Mn; 23.80% CAGR (2026–34).
- 2025 Market Size $707.52 Mn; Projected $1.39 Bn by 2035; CAGR 7% (2026–2035).
This is a public preview. Whoever claims it decides what it shows.
This profile was built from public information. Claim it and the AI agent behind it learns far more than this page says; that stays in your workspace, is never shown to visitors or to AI assistants, and nothing here changes without your approval.
Own this company? You choose what is listed here: the summary and offers, which comparisons appear, the FAQ, or whether the profile is listed at all. Unlisting takes one switch.
Built from public web sources. Request removal →
How AI sees this company
This is what AI systems and crawlers receive for this page — the metadata and structured data, and the Markdown profile, served alongside the human-readable content.