Tensorway vs Deviniti: full comparison for 2026
Last updated: August 2026
Quick verdict
Tensorway (4.8/5) edges ahead of Deviniti (4.0/5) overall. Tensorway is the better choice for enterprises that want a working agent MVP inside a month without ripping out existing systems.. Deviniti is the stronger option for enterprises already on the Atlassian ecosystem that want agentic workflow automation from a known integration partner.. The right choice depends on your project size, budget, and required tech stack.
Tensorway vs Deviniti: head-to-head summary
| Criterion | Tensorway | Deviniti |
|---|---|---|
| Founded | 2019 | 2004 |
| HQ | Alicante, Spain | Wrocław, Poland |
| Team size | 50–249 | 201–500 |
| Rating | 4.8 / 5 | 4.0 / 5 |
| Best for | Enterprises that want a working agent MVP inside a month without ripping out existing systems. | Enterprises already on the Atlassian ecosystem that want agentic workflow automation from a known integration partner. |
| Pricing model | Fixed project, dedicated team, retainer, time & materials, plus a discovery-first exploratory option | Fixed project, dedicated team |
| Min. engagement | $10K (per company website; independently unverifiable) | $20K (per company website; independently unverifiable) |
| Primary tech stack | Python, TypeScript, LangChain | Python, Java, LangChain |
| Industries served | Healthcare, Financial Services, Retail & E-commerce, Manufacturing, Real Estate, Energy | Financial Services, Manufacturing, Technology & SaaS, Retail & E-commerce |
Tensorway vs Deviniti: overview
Tensorway
Tensorway is the AI-focused unit of an established Alicante, Spain software development company with roughly 25 years in the market, spun out specifically to build autonomous and multi-agent systems for enterprise clients. Its six-phase methodology — assessment, lightweight API-first architecture, a progressive build to a working MVP within a month, RAG-based knowledge integration, embedded compliance, and continuous monitoring — is built around plugging into a client's existing stack rather than replacing it. The team of 20+ specialists (DL architects, MLOps engineers, ML engineers, QAs) has delivered agentic work spanning legal document automation, deal-sourcing for private equity, and AI tutoring, and the parent company's decades of delivery history give the AI unit a longer institutional track record than most pure-play agent shops in this list. Claims of "15+ industry-leading AI projects" and "100% compliant development" are per company website; independently unverifiable.
Deviniti
Deviniti is a Wrocław, Poland-based software company founded in 2004 by Piotr Dorosz and Jacek Machata, with roughly 260 employees across Europe and North America. It grew out of enterprise IT solutions for the financial sector and built a significant Atlassian-ecosystem practice (apps and consulting) before extending into broader enterprise software and, more recently, agentic AI. Its AI-agent practice is newer than its Atlassian and enterprise-software work, so buyers should weight recent agent-specific references more heavily than the firm's overall tenure.
Services and capabilities: Tensorway vs Deviniti
| Capability | Tensorway | Deviniti |
|---|---|---|
| Multi-agent orchestration | ✓ | ✗ |
| RAG / knowledge integration | ✓ | ✗ |
| Workflow & systems integration | ✓ | ✓ |
| Coding agents | ✓ | ✗ |
| Monitoring & anomaly detection | ✓ | ✗ |
| Customer-facing agents | ✗ | ✗ |
Tech stack comparison: Tensorway vs Deviniti
| Framework / platform | Tensorway | Deviniti |
|---|---|---|
| LangChain | ✓ | ✓ |
| LangGraph | ✓ | N/A |
| AutoGen | ✓ | N/A |
| LlamaIndex | ✓ | N/A |
| OpenAI | N/A | N/A |
| Anthropic Claude | N/A | N/A |
| Pinecone | ✓ | N/A |
| AWS | ✓ | ✓ |
| Azure | ✓ | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Tensorway vs Deviniti
| Criterion | Tensorway | Deviniti |
|---|---|---|
| Minimum engagement | $10K (per company website; independently unverifiable) | $20K (per company website; independently unverifiable) |
| Engagement models | Fixed project, Dedicated team, Retainer, Time & materials, Discovery-first | Fixed project, Dedicated team |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Accessible | Accessible |
Target audience comparison: Tensorway vs Deviniti
| Dimension | Tensorway | Deviniti |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Healthcare, Financial Services, Retail & E-commerce | Financial Services, Manufacturing, Technology & SaaS |
| Best use cases | Deploying a RAG-backed knowledge agent over proprietary internal documents, Automating a specific high-volume workflow like invoice processing or document review | Building workflow-integration agents for teams already running Atlassian tooling, Automating internal enterprise processes for financial-sector clients |
| Typical project type | Fixed project | Fixed project |
Tensorway vs Deviniti: pros and cons
| Tensorway | |
|---|---|
| + | Six-phase delivery methodology gets a functional MVP live within roughly a month |
| + | Connects into existing ERP/CRM systems rather than requiring a platform overhaul |
| + | Graph-based memory architecture supports genuinely multi-step, not single-turn, reasoning |
| + | Compliance (GDPR, HIPAA, ISO 27001) is embedded in the delivery process, not bolted on after |
| + | Backed by a parent company with two-plus decades of software delivery history |
| - | Team size (50–249, shared across the parent company's broader practice) is smaller than the global systems integrators on this list |
| - | Published case studies are a short list — deal-sourcing, legal automation, ed-tech tutoring — so depth outside those verticals is less proven |
| - | Minimum engagement and project counts are sourced from the company's own site and are independently unverifiable |
| Deviniti | |
|---|---|
| + | Two decades of enterprise systems-integration experience, originally rooted in financial-sector IT |
| + | Established Atlassian-ecosystem practice gives it a natural workflow-integration angle for agents |
| + | ~260-person team spread across Europe and North America for regional delivery coverage |
| + | Founder-led continuity since 2004 provides institutional stability |
| - | Agentic AI is a newer addition to a legacy enterprise-software and Atlassian practice, with a shorter track record than its overall tenure suggests |
| - | Less name recognition in AI-specific buyer circles compared to AI-first competitors |
| - | Public agent-specific case studies are limited relative to its Atlassian portfolio |
Who should choose Tensorway?
Tensorway is the right choice for enterprises that want a working agent MVP inside a month without ripping out existing systems..
Graph-based memory for multi-step reasoning plus a one-month path to a production MVP, without a platform overhaul.. Minimum engagement starts at $10K (per company website; independently unverifiable). Works best with clients in Healthcare, Financial Services, Retail & E-commerce, Manufacturing, Real Estate, Energy.
Who should choose Deviniti?
Deviniti is the right choice for enterprises already on the Atlassian ecosystem that want agentic workflow automation from a known integration partner..
Two decades of enterprise systems-integration work, including deep Atlassian-ecosystem expertise, applied to agent workflow integration.. Minimum engagement starts at $20K (per company website; independently unverifiable). Works best with clients in Financial Services, Manufacturing, Technology & SaaS, Retail & E-commerce.
Decision matrix: Tensorway vs Deviniti
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Tensorway |
| You need a large dedicated team for an ongoing programme | Tensorway |
| Your budget is at the lower end | Tensorway |
| You need specialist depth in a specific vertical | Tensorway |
| You need staff augmentation or team extension | Neither; consider alternatives that offer staff aug |
| You need consulting before committing to a build | Both may offer discovery engagements |
Use case fit: Tensorway vs Deviniti
| Use case | Tensorway fit | Deviniti fit | Winner |
|---|---|---|---|
| Deploying a RAG-backed knowledge agent over proprietary internal documents | Strong | Limited | Tensorway |
| Automating a specific high-volume workflow like invoice processing or document review | Strong | Strong | Both equally |
| Building workflow-integration agents for teams already running Atlassian tooling | Strong | Strong | Both equally |
| Automating internal enterprise processes for financial-sector clients | Strong | Strong | Both equally |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Tensorway vs Deviniti
Tensorway (4.8/5) is the stronger overall choice for most AI Agent Development projects. Graph-based memory for multi-step reasoning plus a one-month path to a production MVP, without a platform overhaul.. It is best for enterprises that want a working agent MVP inside a month without ripping out existing systems..
Deviniti (4.0/5) is the better choice when enterprises already on the Atlassian ecosystem that want agentic workflow automation from a known integration partner.. If your situation matches those criteria, Deviniti is a competitive option.
Related comparisons
Tensorway vs Deviniti FAQ
Is Tensorway better than Deviniti?
Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway is better for enterprises that want a working agent MVP inside a month without ripping out existing systems.. Deviniti is better for enterprises already on the Atlassian ecosystem that want agentic workflow automation from a known integration partner..
How do Tensorway and Deviniti differ in pricing?
Tensorway uses fixed project, dedicated team, retainer, time & materials, plus a discovery-first exploratory option pricing with a minimum engagement of $10K (per company website; independently unverifiable). Deviniti uses fixed project, dedicated team pricing with a minimum engagement of $20K (per company website; independently unverifiable). Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Tensorway or Deviniti?
Deviniti is the larger team and typically the better enterprise-scale choice. For very large programmes, verify team size and compliance coverage directly with each company before shortlisting.
What are the main differences between Tensorway and Deviniti?
Tensorway's primary differentiator is: graph-based memory for multi-step reasoning plus a one-month path to a production mvp, without a platform overhaul.. Deviniti's primary differentiator is: two decades of enterprise systems-integration work, including deep atlassian-ecosystem expertise, applied to agent workflow integration.. They also differ in team size (50–249 vs 201–500), minimum engagement ($10K (per company website; independently unverifiable) vs $20K (per company website; independently unverifiable)), and primary industries served (Healthcare, Financial Services vs Financial Services, Manufacturing).
Last reviewed: August 2026. Verify all details directly with each company before making a decision.