Gradient Labs vs Endava: full comparison for 2026
Last updated: August 2026
Quick verdict
Gradient Labs (4.3/5) edges ahead of Endava (4.0/5) overall. Gradient Labs is the better choice for uK and European financial-services firms wanting a narrow, deeply regulatory-fluent autonomous customer-operations agent.. Endava is the stronger option for uK and European enterprises wanting a vendor that has publicly documented using agentic AI on its own internal delivery methodology.. The right choice depends on your project size, budget, and required tech stack.
Gradient Labs vs Endava: head-to-head summary
| Criterion | Gradient Labs | Endava |
|---|---|---|
| Founded | 2023 | 2000 |
| HQ | London, UK | London, UK |
| Team size | 11–50 | 10,000+ |
| Rating | 4.3 / 5 | 4.0 / 5 |
| Best for | UK and European financial-services firms wanting a narrow, deeply regulatory-fluent autonomous customer-operations agent. | UK and European enterprises wanting a vendor that has publicly documented using agentic AI on its own internal delivery methodology. |
| Pricing model | Retainer, platform licensing | Dedicated team, retainer, time & materials |
| Min. engagement | Not published | Not published |
| Primary tech stack | Python, LangChain, OpenAI | Python, OpenAI, LangChain |
| Industries served | Financial Services, Banking | Financial Services, Technology & SaaS, Retail & E-commerce, Healthcare |
Gradient Labs vs Endava: overview
Gradient Labs
Gradient Labs is a London-based startup founded in 2023 by former Monzo Bank employees Dimitri Masin, Neal Lathia, and Danai Antoniou, with roughly 46 employees and $13M+ in Series A funding at a $60M valuation. Its flagship product, Otto, is an autonomous agent purpose-built for customer operations in regulated financial services, engineered to resolve complex queries end-to-end while maintaining compliance, reportedly achieving up to a 90% resolution rate with a 98% QA pass rate. Its narrow, financial-services-specific focus and UK domicile make it a fit for buyers wanting deep regulatory fluency over broad horizontal agent capability.
Endava
Endava was founded in 2000 and is headquartered in London, UK, with over 10,000 employees across 26 locations. It has embedded OpenAI's AI agents directly into its own software delivery workflow, branded as DavaFlow, making it one of the few firms on this list that has publicly documented using agentic AI to redesign its own internal delivery process, not just sell it to clients. As a UK-headquartered, NYSE-listed company, it offers public financial disclosure but sits outside EU jurisdiction post-Brexit for its own corporate entity.
Services and capabilities: Gradient Labs vs Endava
| Capability | Gradient Labs | Endava |
|---|---|---|
| Multi-agent orchestration | ✗ | ✓ |
| RAG / knowledge integration | ✗ | ✗ |
| Workflow & systems integration | ✓ | ✓ |
| Coding agents | ✗ | ✓ |
| Monitoring & anomaly detection | ✓ | ✗ |
| Customer-facing agents | ✓ | ✗ |
Tech stack comparison: Gradient Labs vs Endava
| Framework / platform | Gradient Labs | Endava |
|---|---|---|
| LangChain | ✓ | ✓ |
| LangGraph | N/A | N/A |
| AutoGen | N/A | N/A |
| LlamaIndex | N/A | N/A |
| OpenAI | ✓ | ✓ |
| Anthropic Claude | ✓ | N/A |
| Pinecone | N/A | N/A |
| AWS | ✓ | ✓ |
| Azure | N/A | ✓ |
| Kubernetes | N/A | N/A |
Pricing comparison: Gradient Labs vs Endava
| Criterion | Gradient Labs | Endava |
|---|---|---|
| Minimum engagement | Not published | Not published |
| Engagement models | Retainer | Dedicated team, Retainer, Time & materials |
| Rate transparency | Minimum disclosed | Minimum disclosed |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Gradient Labs vs Endava
| Dimension | Gradient Labs | Endava |
|---|---|---|
| Best company size | Startup to mid-market | Enterprise |
| Best industries | Financial Services, Banking | Financial Services, Technology & SaaS, Retail & E-commerce |
| Best use cases | Regulated financial-services firms wanting a purpose-built autonomous customer-operations agent, Banking or insurance clients needing compliance-fluent agent behavior out of the box | Buyers wanting proof a vendor applies agentic AI to its own delivery process before selling it externally, UK and European enterprises needing large-scale dedicated-team engagements |
| Typical project type | Retainer | Dedicated team |
Gradient Labs vs Endava: pros and cons
| Gradient Labs | |
|---|---|
| + | Founding team's direct experience at Monzo (a regulated UK bank) feeds real compliance fluency into Otto |
| + | Named, benchmarked production agent with disclosed resolution-rate and QA-pass-rate figures |
| + | Venture-backed ($13M+ Series A) with runway to keep investing in the product |
| + | UK domicile with a narrow, deep focus on regulated financial services specifically |
| - | Very narrow focus (financial-services customer operations) — not a fit for other verticals or broader custom agent builds |
| - | Small team (~46 employees) limits capacity and account-management bandwidth |
| - | As a product company rather than a services firm, engagement is closer to platform licensing than bespoke development |
| Endava | |
|---|---|
| + | Publicly documented use of OpenAI's agentic AI in its own internal delivery methodology (DavaFlow) |
| + | NYSE-listed with public financial disclosure |
| + | 10,000+ employees across 26 locations gives substantial bench depth |
| + | Quarter-century of digital consultancy history since 2000 |
| - | UK-headquartered, so post-Brexit it sits outside EU jurisdiction for its own corporate entity |
| - | Minimum engagement figures are not published, requiring direct sales contact for early budgeting |
| - | 26-location scale can mean less senior-architect access than boutique competitors |
Who should choose Gradient Labs?
Gradient Labs is the right choice for uK and European financial-services firms wanting a narrow, deeply regulatory-fluent autonomous customer-operations agent..
Otto, a named production agent for regulated financial-services customer operations, built by founders with direct Monzo banking-compliance experience.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Banking.
Who should choose Endava?
Endava is the right choice for uK and European enterprises wanting a vendor that has publicly documented using agentic AI on its own internal delivery methodology..
A named, OpenAI-powered internal delivery methodology (DavaFlow) — evidence the firm applies agentic AI to its own software delivery, not just client work.. Minimum engagement starts at Not published. Works best with clients in Financial Services, Technology & SaaS, Retail & E-commerce, Healthcare.
Decision matrix: Gradient Labs vs Endava
| Your situation | Recommended choice |
|---|---|
| You need full-ownership delivery on a defined project scope | Both offer fixed-price models |
| You need a large dedicated team for an ongoing programme | Endava |
| Your budget is at the lower end | Compare: Gradient Labs (Not published) vs Endava (Not published) |
| You need specialist depth in a specific vertical | Endava |
| 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: Gradient Labs vs Endava
| Use case | Gradient Labs fit | Endava fit | Winner |
|---|---|---|---|
| Regulated financial-services firms wanting a purpose-built autonomous customer-operations agent | Strong | Limited | Gradient Labs |
| Banking or insurance clients needing compliance-fluent agent behavior out of the box | Strong | Limited | Gradient Labs |
| Buyers wanting proof a vendor applies agentic AI to its own delivery process before selling it externally | Strong | Strong | Both equally |
| UK and European enterprises needing large-scale dedicated-team engagements | Limited | Strong | Endava |
| Fixed-price build | Limited | Limited | Both equally |
| Staff augmentation | Limited | Limited | Both equally |
Verdict: Gradient Labs vs Endava
Gradient Labs (4.3/5) is the stronger overall choice for most AI Agent Development projects. Otto, a named production agent for regulated financial-services customer operations, built by founders with direct Monzo banking-compliance experience.. It is best for uK and European financial-services firms wanting a narrow, deeply regulatory-fluent autonomous customer-operations agent..
Endava (4.0/5) is the better choice when uK and European enterprises wanting a vendor that has publicly documented using agentic AI on its own internal delivery methodology.. If your situation matches those criteria, Endava is a competitive option.
Related comparisons
Gradient Labs vs Endava FAQ
Is Gradient Labs better than Endava?
Gradient Labs (4.3/5) scores higher overall, but "better" depends on your use case. Gradient Labs is better for uK and European financial-services firms wanting a narrow, deeply regulatory-fluent autonomous customer-operations agent.. Endava is better for uK and European enterprises wanting a vendor that has publicly documented using agentic AI on its own internal delivery methodology..
How do Gradient Labs and Endava differ in pricing?
Gradient Labs uses retainer, platform licensing pricing with a minimum engagement of Not published. Endava uses dedicated team, retainer, time & materials pricing with a minimum engagement of Not published. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Gradient Labs or Endava?
Endava 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 Gradient Labs and Endava?
Gradient Labs's primary differentiator is: otto, a named production agent for regulated financial-services customer operations, built by founders with direct monzo banking-compliance experience.. Endava's primary differentiator is: a named, openai-powered internal delivery methodology (davaflow) — evidence the firm applies agentic ai to its own software delivery, not just client work.. They also differ in team size (11–50 vs 10,000+), minimum engagement (Not published vs Not published), and primary industries served (Financial Services, Banking vs Financial Services, Technology & SaaS).
Last reviewed: August 2026. Verify all details directly with each company before making a decision.