Turing
AI-powered talent marketplace for sourcing and deploying vetted AI engineering teams
What is Turing?
Turing (founded 2018, Palo Alto CA) is a talent marketplace, not a development firm. Its platform sources and vets engineers from a network of over 3 million developers across 150+ countries, then deploys them as dedicated remote teams to client companies. Turing does not own project outcomes, set technical direction, or deliver a defined scope — the client engineering leadership does. This model is well suited to companies that need to scale an existing AI team quickly with pre-vetted remote talent. It is not the right fit for buyers who need a vendor to take full delivery ownership of an AI agent project from architecture to production.
Turing was founded in 2018 and is headquartered in Palo Alto, CA, USA. The firm employs 1,000+ (platform staff); 3M+ vetted developer network people and works primarily with clients in SaaS, Fintech, E-commerce, Media sectors. Its primary differentiator is: Talent marketplace: assembles a vetted AI engineering team in days; buyer must provide technical direction and project ownership.
Turing tech stack and services
| Service area | Details |
|---|---|
| Scaling an existing AI engineering team with specialist contractors | Available for SaaS, Fintech, E-commerce, Media clients |
| Building an in-house AI capability quickly alongside an internal lead | Available for SaaS, Fintech, E-commerce, Media clients |
| Augmenting a product team with a dedicated AI engineering pod | Available for SaaS, Fintech, E-commerce, Media clients |
Turing use cases
Short answer: Turing is best suited for companies that already have technical leadership and want to scale their AI engineering team quickly with pre-vetted remote talent — not a fit for outsourced delivery ownership.
| Use case | Industries | Approach |
|---|---|---|
| Scaling an existing AI engineering team with specialist contractors | SaaS, Fintech | OpenAI, LangChain |
| Building an in-house AI capability quickly alongside an internal lead | SaaS, Fintech | OpenAI, LangChain |
| Augmenting a product team with a dedicated AI engineering pod | SaaS, Fintech | OpenAI, LangChain |
Turing pricing
Short answer: Turing uses a dedicated team, t&m pricing approach. Minimum engagement starts at Varies by team size (approx. $8K–$20K/month per engineer).
| Engagement model | Typical range | Best for |
|---|---|---|
| Dedicated team | Variable; depends on team size | Large programmes or team augmentation |
| Time and materials | Variable; depends on team size | Large programmes or team augmentation |
Turing pros and cons
| Advantages | Things to consider |
|---|---|
| +Fast team assembly: vetted AI engineers placed within days rather than months | -Not a delivery firm: Turing does not own project outcomes or provide technical direction |
| +Flexible scaling: adjust team size month-to-month | -Requires internal technical leadership to manage; a poor fit if you lack AI engineering oversight |
| +Access to global talent pool; competitive hourly rates for specialisms | -No fixed-price project model; no delivery guarantee |
| -Engineers are platform-vetted; quality varies by individual; expect onboarding ramp |
Turing vs alternatives
How Turing compares to the other top AI agent development companies in 2026.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | SaaS companies and tech teams that need a... | AI-native from founding: every engineer is an agent specialist, not a repositioned generalist | 4.9 | Full comparison |
| Leewayhertz | Mid-market product and engineering teams that need AI-first... | Broadest framework coverage (LangGraph, CrewAI, AutoGen) and largest completed AI portfolio of the specialist firms on this list | 4.6 | Full comparison |
| EPAM Systems | Enterprise organisations (1,000+ employees) needing scalable AI engineering... | 55,000+ engineers, top-tier partnerships with AWS / Azure / GCP, and a track record in compliance-sensitive regulated-industry AI deployments | 4.5 | Full comparison |
| SoftServe | Mid-market to enterprise teams needing GenAI or healthcare... | Deep healthcare AI delivery track record alongside 30+ years of IT services; primary engineering base in Ukraine and Poland | 4.2 | Full comparison |
| Appinventiv | Cost-conscious projects needing a fixed-scope AI agent or... | India-based delivery rates with a 1,500+ team; accessible fixed-price model for defined-scope AI builds | 3.7 | Full comparison |
| SoluLab | Startups and early-stage teams exploring AI agent feasibility... | Lowest minimum engagement ($15K) of any firm on this list; accessible starting point before committing to larger AI-native vendors | 3.5 | Full comparison |
| Simform | Mid-market and enterprise teams needing cloud-native AI agent... | 1,000+ engineers with AWS, Google Cloud, and Azure partnerships; strong client satisfaction track record on Clutch | 4.6 | Full comparison |
| Markovate | Healthcare, fintech, and SaaS companies integrating AI agents... | ISO-certified with HIPAA/GDPR readiness; leadership with prior AI experience at AT&T and IBM | 4.5 | Full comparison |
| Kanerika | Mid-market and enterprise companies in manufacturing, logistics, and... | Microsoft Solutions Partner for Data & AI; data-native agent design on top of existing data pipelines | 4.5 | Full comparison |
| ITRex Group | Media, fintech, and SaaS companies needing AI-first engineering... | AI-first engineering culture with US + EMEA delivery and no long-term lock-in; start-small PoC model | 4.4 | Full comparison |
| Intuz | Healthcare, e-commerce, and finance teams needing multimodal AI... | Cross-framework expertise across five agent frameworks (LangGraph, AutoGen, CrewAI, OpenAgents, MetaGPT) and multimodal agent support | 4.4 | Full comparison |
| Brocoders | SaaS companies and mid-sized businesses that need AI... | 5.0 Clutch rating across 30 reviews; MCP-enabled AI workflows in production products | 4.8 | Full comparison |
| Azumo | US product teams seeking nearshore AI engineering with... | Nearshore Latin America delivery with US time zones; SOC 2 compliant private model tuning | 4.4 | Full comparison |
| DevCom | Mid-market businesses building custom AI agents for defined... | Close-collaboration delivery model; US-based client management with Ukraine-based engineering | 4.3 | Full comparison |
| Neurons Lab | Financial institutions and regulated-sector organisations moving AI agents... | Financial services specialisation with compliance and data sovereignty built into every delivery | 4.5 | Full comparison |
| RTS Labs | Enterprise teams needing combined data strategy and AI... | Data strategy and AI agent development in one firm; supply chain and logistics AI depth | 4.3 | Full comparison |
| Master of Code Global | Enterprise retail, banking, and healthcare teams building customer-facing... | 10+ years of conversational AI delivery; 250+ projects across enterprise clients | 4.4 | Full comparison |
| HatchWorks AI | Healthcare, financial services, and energy organisations that need... | Governance and model observability built into the architecture from sprint one | 4.3 | Full comparison |
| Intellectyx | Enterprise organisations that need AI agents mapped to... | Strategy-led approach: AI agents are scoped against business outcomes, not technology requirements | 4.2 | Full comparison |
| SoftKraft | SaaS and tech companies that prioritise code quality... | Test-driven development (TDD) methodology applied to AI agents — validated before production deployment | 4.3 | Full comparison |
| Codebridge | Tech companies building AI agents as a core... | Architectural-first methodology: AI agents designed as a foundational system layer, not a bolt-on | 4.3 | Full comparison |
| Neoteric | Companies building AI agents where end-user experience is... | AI-native consultancy with UX depth — agents designed for user adoption, not just technical performance | 4.2 | Full comparison |
| OpenKit | Legal, education, and regulated-sector organisations needing AI agents... | Legal and edtech AI agent specialisation with data sovereignty and compliance focus | 4.2 | Full comparison |
| GenAI Labs | Businesses needing production-ready AI agents for internal workflow... | Production-first philosophy: every engagement targets real business system integration, not generic LLM demos | 4.3 | Full comparison |
| XenonStack | Enterprise teams needing AI agents embedded in cloud-native... | Platform engineering depth — AI agents built on top of production-grade cloud and data infrastructure | 4.1 | Full comparison |
| Deeper Insights | UK and European organisations needing AI agent development... | UK-based AI and data science depth with AI governance consulting; strong NLP and computer vision background | 4.2 | Full comparison |
| LITSLINK | SaaS, fintech, and healthcare teams needing production-grade AI... | Multi-framework expertise across 5 agent frameworks with observability tooling built into every deployment | 4.2 | Full comparison |
| AscentCore | Enterprise teams needing AI agents integrated with existing... | Product thinking applied to AI engineering — agents designed for operational integration, not standalone deployment | 4.1 | Full comparison |
| ScienceSoft | Enterprise organisations that need AI agent development backed... | 35 years of IT delivery experience with a mature AI and ML practice; strong risk management and project governance | 4.3 | Full comparison |
Turing FAQ
What is Turing?
Turing (founded 2018, Palo Alto CA) is a talent marketplace, not a development firm. Its platform sources and vets engineers from a network of over 3 million developers across 150+ countries, then deploys them as dedicated remote teams to client companies. Turing does not own project outcomes, set technical direction, or deliver a defined scope — the client engineering leadership does. This model is well suited to companies that need to scale an existing AI team quickly with pre-vetted remote talent. It is not the right fit for buyers who need a vendor to take full delivery ownership of an AI agent project from architecture to production.
How much does Turing charge?
Turing uses dedicated team, t&m pricing. Minimum engagement starts at Varies by team size (approx. $8K–$20K/month per engineer). A discovery call is required to get project-specific quotes.
What tech stack does Turing use?
Turing works with OpenAI, LangChain, Python, React, Node.js, AWS, GCP. Primary industries served include SaaS, Fintech, E-commerce, Media.
Is Turing right for enterprise?
Companies that already have technical leadership and want to scale their AI engineering team quickly with pre-vetted remote talent — not a fit for outsourced delivery ownership. 1,000+ (platform staff); 3M+ vetted developer network team size. Key consideration: Not a delivery firm: Turing does not own project outcomes or provide technical direction.
What are the best Turing alternatives?
The best alternatives to Turing depend on your use case. Top options are:
- Tensorway: ai-native from founding: every engineer is an agent specialist, not a repositioned generalist
- Leewayhertz: broadest framework coverage (langgraph, crewai, autogen) and largest completed ai portfolio of the specialist firms on this list
- EPAM Systems: 55,000+ engineers, top-tier partnerships with aws / azure / gcp, and a track record in compliance-sensitive regulated-industry ai deployments
Compare Turing with other AI agent development companies
Last reviewed: June 2026. Verify all details directly with Turing before making a decision.