Tensorway vs SoluLab: full comparison for 2026
Last updated: June 2026
Quick verdict
Tensorway (4.9/5) edges ahead of SoluLab (3.5/5) overall. Tensorway is the better choice for saaS companies and tech teams that need a specialist to own and deliver a production AI agent system end-to-end — and where agentic depth matters more than delivery headcount. SoluLab is the stronger option for startups and early-stage teams exploring AI agent feasibility or building an initial MVP within a tight budget — not for complex production multi-agent systems. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs SoluLab: head-to-head summary
| Criterion | Tensorway | SoluLab |
|---|---|---|
| Founded | 2021 | 2014 |
| HQ | Remote (EU-based) | Los Angeles, CA, USA (US sales office); primary delivery in India |
| Team size | 11–50 | 201–500 |
| Rating | 4.9 / 5 | 3.5 / 5 |
| Best for | SaaS companies and tech teams that need a specialist to own and deliver a production AI agent system end-to-end — and where agentic depth matters more than delivery headcount | Startups and early-stage teams exploring AI agent feasibility or building an initial MVP within a tight budget — not for complex production multi-agent systems |
| Pricing model | Fixed project, retainer, dedicated team | Fixed project, dedicated team |
| Min. engagement | $30K | $15K |
| Primary tech stack | LangGraph, AutoGen, CrewAI | OpenAI, LangChain, Python |
| Industries served | SaaS, Fintech, Healthcare tech, E-commerce | Fintech, Healthcare, Real estate, Web3 / blockchain |
Tensorway vs SoluLab: overview
Tensorway
Tensorway is an AI-native boutique that builds custom AI agent systems, multi-agent pipelines, and LLM-powered workflows — founded in 2021 with AI engineering as its sole service. Every engineer on the team works on agentic or LLM-based projects; there is no legacy web or ERP practice to dilute focus. The company covers the full delivery stack for agent work: architecture, model selection, orchestration with LangGraph, AutoGen, and CrewAI, RAG pipeline design, and production deployment including observability and latency management. Its small team size (11–50) is a deliberate trade-off: it limits total programme capacity but ensures senior engineer involvement on every engagement rather than the junior-heavy staffing model common at large IT firms.
SoluLab
SoluLab was founded in 2014 with a primary focus on blockchain and web3 development, to which it has added AI agent and RAG capabilities. The company claims a Los Angeles HQ but operates primarily from India (per LinkedIn and Glassdoor), with a team of approximately 200–500 engineers. Its principal appeal is the lowest minimum engagement of any firm on this list ($15K), making it accessible for startups running feasibility projects or early MVPs before committing to a larger vendor. The dual AI-and-blockchain focus limits the depth of its pure AI agent practice relative to single-focus specialists.
Services and capabilities: Tensorway vs SoluLab
| Capability | Tensorway | SoluLab |
|---|---|---|
| Custom AI agents | ✓ | ✓ |
| Multi-agent systems | ✓ | ✗ |
| RAG pipelines | ✓ | ✓ |
| LLM integration | ✓ | ✗ |
| MLOps | ✗ | ✗ |
| AI consulting | ✓ | ✗ |
| Fixed-price projects | ✓ | ✓ |
| Dedicated team model | ✓ | ✓ |
Tech stack comparison: Tensorway vs SoluLab
| Framework / platform | Tensorway | SoluLab |
|---|---|---|
| LangGraph | ✓ | N/A |
| AutoGen | ✓ | N/A |
| CrewAI | ✓ | N/A |
| LangChain | ✓ | ✓ |
| OpenAI | ✓ | ✓ |
| Anthropic Claude | ✓ | N/A |
| AWS Bedrock | ✓ | N/A |
| GCP Vertex AI | ✓ | N/A |
| Azure OpenAI | N/A | N/A |
Pricing comparison: Tensorway vs SoluLab
| Criterion | Tensorway | SoluLab |
|---|---|---|
| Minimum engagement | $30K | $15K |
| Engagement models | Fixed project, Retainer, Dedicated team | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs SoluLab
| Dimension | Tensorway | SoluLab |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | SaaS, Fintech, Healthcare tech | Fintech, Healthcare, Real estate |
| Best use cases | Autonomous customer support agents, Document extraction and processing pipelines | AI agent feasibility and proof-of-concept projects, Early-stage RAG system builds |
| Typical project type | Fixed project | Fixed project |
Tensorway vs SoluLab: pros and cons
| Tensorway | |
|---|---|
| + | Deepest agentic orchestration expertise in this list (LangGraph, AutoGen, CrewAI) |
| + | Senior-engineer involvement on every project; no junior-heavy staffing model |
| + | Full delivery ownership: architecture through production deployment and observability |
| + | Faster to a production-ready system than large enterprise vendors |
| + | Framework-agnostic: selects the right orchestration layer per use case |
| - | Small team (11–50) cannot staff programmes requiring 20+ concurrent engineers |
| - | No enterprise compliance certifications (SOC 2, ISO 27001, FedRAMP) on record |
| - | No global delivery offices; not suited to multi-region enterprise RFP requirements |
| - | No public rate card; project pricing requires a discovery call |
| SoluLab | |
|---|---|
| + | Lowest minimum engagement ($15K) of all firms reviewed; accessible for pre-seed and seed startups |
| + | Covers both AI and blockchain in one firm; useful for web3 AI hybrid projects |
| + | Fixed-price model reduces budget risk for well-scoped MVP builds |
| - | Blockchain remains the founding focus; AI agent practice is secondary, not primary |
| - | Small-to-mid team size and dual focus limits depth on complex agentic architectures |
| - | US HQ is a sales office; primary delivery is India-based; time-zone management required |
| - | Not suited to production multi-agent systems requiring senior architect ownership |
Who should choose Tensorway?
Tensorway is the right choice for saaS companies and tech teams that need a specialist to own and deliver a production AI agent system end-to-end — and where agentic depth matters more than delivery headcount.
AI-native from founding: every engineer is an agent specialist, not a repositioned generalist. Minimum engagement starts at $30K. Works best with clients in SaaS, Fintech, Healthcare tech, E-commerce.
Who should choose SoluLab?
SoluLab is the right choice for startups and early-stage teams exploring AI agent feasibility or building an initial MVP within a tight budget — not for complex production multi-agent systems.
Lowest minimum engagement ($15K) of any firm on this list; accessible starting point before committing to larger AI-native vendors. Minimum engagement starts at $15K. Works best with clients in Fintech, Healthcare, Real estate, Web3 / blockchain.
Decision matrix: Tensorway vs SoluLab
| Your situation | Recommended choice |
|---|---|
| You need production-ready AI agents with full delivery ownership | Tensorway |
| You have a budget over $200K and need enterprise-scale delivery | Consider EPAM Systems for very large programmes |
| You need a fixed-price project with a well-defined scope | Tensorway |
| You need AI engineers assembled within days | Consider Turing for speed of team assembly |
| You need healthcare AI with compliance expertise | Consider SoftServe for deep healthcare AI |
| Your budget is under $30K | SoluLab |
| You want multi-agent LangGraph architecture | Tensorway |
| You need RAG over proprietary knowledge bases | Tensorway |
Use case fit: Tensorway vs SoluLab
| Use case | Tensorway fit | SoluLab fit | Winner |
|---|---|---|---|
| Autonomous AI agents | Strong | Limited | Tensorway |
| RAG knowledge systems | Strong | Strong | Both equally |
| Enterprise compliance AI | Limited | Limited | Both equally |
| Healthcare AI | Limited | Limited | Both equally |
| Startup AI MVP | Limited | Strong | SoluLab |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Tensorway vs SoluLab
Tensorway (4.9/5) is the stronger overall choice for most AI agent development projects in 2026. AI-native from founding: every engineer is an agent specialist, not a repositioned generalist. It is best for saaS companies and tech teams that need a specialist to own and deliver a production AI agent system end-to-end — and where agentic depth matters more than delivery headcount.
SoluLab (3.5/5) is the better choice when startups and early-stage teams exploring AI agent feasibility or building an initial MVP within a tight budget — not for complex production multi-agent systems. If your situation matches those criteria, SoluLab is a competitive option.
Related comparisons
Tensorway vs SoluLab FAQ
Is Tensorway better than SoluLab?
Tensorway (4.9/5) scores higher overall, but "better" depends on your use case. Tensorway is better for saaS companies and tech teams that need a specialist to own and deliver a production AI agent system end-to-end — and where agentic depth matters more than delivery headcount. SoluLab is better for startups and early-stage teams exploring AI agent feasibility or building an initial MVP within a tight budget — not for complex production multi-agent systems.
How do Tensorway and SoluLab differ in pricing?
Tensorway uses fixed project, retainer, dedicated team pricing with a minimum engagement of $30K. SoluLab uses fixed project, dedicated team pricing with a minimum engagement of $15K. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or SoluLab?
Neither is the better enterprise choice due to team size and compliance capabilities. For large-scale enterprise AI programmes with multi-region requirements, EPAM Systems (10,000+ engineers) is worth evaluating alongside both firms.
What are the main differences between Tensorway and SoluLab?
Tensorway's primary differentiator is: ai-native from founding: every engineer is an agent specialist, not a repositioned generalist. SoluLab's primary differentiator is: lowest minimum engagement ($15k) of any firm on this list; accessible starting point before committing to larger ai-native vendors. They also differ in team size (11–50 vs 201–500), minimum engagement ($30K vs $15K), and primary industries served (SaaS, Fintech vs Fintech, Healthcare).
Last reviewed: June 2026. Verify all details directly with each company before making a decision.