Avanade vs deepsense.ai: full comparison for 2026
Quick verdict
Avanade (4.4/5) edges ahead of deepsense.ai (4.4/5) overall. Avanade is the better choice for microsoft-standardized enterprises rolling out Copilot. deepsense.ai is the stronger option for engineering teams wanting a strong RAG partner. The right choice depends on your project size, budget, and required tech stack.
Avanade vs deepsense.ai: head-to-head summary
| Criterion | Avanade | deepsense.ai |
|---|---|---|
| Founded | 2000 | 2014 |
| HQ | Seattle, WA, USA | Warsaw, Poland |
| Team size | 50,000+ | 101–200 |
| Rating | 4.4 / 5 | 4.4 / 5 |
| Primary differentiator | A Microsoft-only practice of about 59,000 people covering Dynamics 365, Azure OpenAI and Copilot governance | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets |
| Pricing model | Enterprise consulting rates, fixed-scope programmes and managed services; rates on request | T&M and dedicated teams; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Microsoft Dynamics 365, Azure OpenAI, Microsoft Copilot | LangChain, Azure OpenAI, AWS Bedrock |
| Industries served | Financial services, Retail, Manufacturing, Public sector, Healthcare | Manufacturing, Retail, Financial services, Healthcare |
Avanade vs deepsense.ai: overview
Avanade
Avanade was formed in April 2000 as a joint venture between Accenture (then Andersen Consulting) and Microsoft, and it is now majority-owned by Accenture. Headquartered in Seattle, it reports about 59,000 professionals in 26 countries. It works almost exclusively on the Microsoft platform, which gives it unusual depth in Dynamics 365, Azure OpenAI Service, Power Platform and Copilot deployments. The catch is plain: its advice rarely leaves Microsoft.
deepsense.ai
deepsense.ai is an AI-first engineering company founded in 2014 out of the AI division of CodiLime, with headquarters in Warsaw and an office in Palo Alto. It employs roughly 120–200 people, including several Kaggle competition winners. Its integration work centres on LLM applications using retrieval-augmented generation (RAG), plus computer vision and edge deployments for manufacturing. It lists technical partnerships with OpenAI, NVIDIA, Anyscale and LangChain.
Services and capabilities: Avanade vs deepsense.ai
| Capability | Avanade | deepsense.ai |
|---|---|---|
| CRM / ERP integration | ✓ | ✗ |
| LLM API gateway & cost control | ✓ | ✓ |
| Document processing | ✗ | ✓ |
| Agentic workflows | ✗ | ✓ |
| Fixed-price pilot | ✗ | ✗ |
| Managed services after launch | ✓ | ✗ |
| PII masking & access control | ✓ | ✗ |
Tech stack comparison: Avanade vs deepsense.ai
| Framework / platform | Avanade | deepsense.ai |
|---|---|---|
| Salesforce | N/A | N/A |
| SAP | N/A | N/A |
| Microsoft Dynamics 365 | ✓ | N/A |
| HubSpot | N/A | N/A |
| Snowflake | N/A | N/A |
| Databricks | N/A | N/A |
| Azure OpenAI | ✓ | ✓ |
| AWS Bedrock | N/A | ✓ |
| LangChain | N/A | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: Avanade vs deepsense.ai
| Criterion | Avanade | deepsense.ai |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed project, Time & materials, Managed services | Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Avanade vs deepsense.ai
| Dimension | Avanade | deepsense.ai |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Financial services, Retail, Manufacturing | Manufacturing, Retail, Financial services |
| Best use cases | Rolling out Microsoft 365 Copilot with data-loss and sensitivity labels configured first., Adding Azure OpenAI features to Dynamics 365 sales and service. | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. |
| Typical project type | Fixed project | Time & materials |
Avanade vs deepsense.ai: pros and cons
| Avanade | |
|---|---|
| + | Microsoft depth that runs from licensing questions to Purview data-loss rules for Copilot |
| + | Can run AI services after launch under a managed contract |
| + | Global delivery centres support follow-the-sun operations |
| + | Backed by Accenture's industry practices when a programme needs them |
| - | Majority-owned by Accenture, so it is effectively part of a larger systems integrator |
| - | Rarely recommends anything outside Microsoft, which narrows options for mixed estates |
| - | Pricing and programme size are built for large enterprises |
| deepsense.ai | |
|---|---|
| + | Deep ML talent, with evaluation of retrieval quality treated as part of the build |
| + | Experience deploying models on edge hardware as well as in the cloud |
| + | Open publication record and active LangChain contribution history |
| + | Comfortable working alongside an in-house data team |
| - | Less experience embedding AI inside packaged CRM or ERP products |
| - | Engagements lean toward engineering capacity, with less change-management support |
Who should choose Avanade?
A typical fit: rolling out Microsoft 365 Copilot with data-loss and sensitivity labels configured first.
A Microsoft-only practice of about 59,000 people covering Dynamics 365, Azure OpenAI and Copilot governance. Minimum engagement is not publicly disclosed. Works best with clients in Financial services, Retail, Manufacturing, Public sector, Healthcare.
Who should choose deepsense.ai?
A typical fit: retrieval assistants over technical manuals or internal knowledge bases.
Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. Minimum engagement is not publicly disclosed. Works best with clients in Manufacturing, Retail, Financial services, Healthcare.
Decision matrix: Avanade vs deepsense.ai
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Neither advertises one; ask for a scoped pilot |
| AI has to work inside your existing CRM or ERP | Avanade |
| Personal data must be masked and answers limited by user permissions | Avanade |
| Your budget is at the lower end | Compare: Avanade (Not disclosed) vs deepsense.ai (Not disclosed) |
| You want the vendor to run the AI service after launch | Avanade |
| You are building multi-step agents across systems | deepsense.ai |
Use case fit: Avanade vs deepsense.ai
| Use case | Avanade fit | deepsense.ai fit | Winner |
|---|---|---|---|
| Rolling out Microsoft 365 Copilot with data-loss and sensitivity labels configured first. | Strong | Limited | Avanade |
| Adding Azure OpenAI features to Dynamics 365 sales and service. | Strong | Limited | Avanade |
| Retrieval assistants over technical manuals or internal knowledge bases. | Limited | Strong | deepsense.ai |
| Visual defect detection on production lines with edge inference. | Limited | Strong | deepsense.ai |
Verdict: Avanade vs deepsense.ai
Avanade (4.4/5) is the stronger overall choice for most AI Integration projects. A Microsoft-only practice of about 59,000 people covering Dynamics 365, Azure OpenAI and Copilot governance.
deepsense.ai (4.4/5) is worth a look if you need visual defect detection on production lines with edge inference. If your situation matches that, deepsense.ai is a competitive option.
Related comparisons
Avanade vs deepsense.ai FAQ
Is Avanade better than deepsense.ai?
Avanade (4.4/5) scores higher overall, but "better" depends on your use case. Avanade's strongest advantage: microsoft depth that runs from licensing questions to Purview data-loss rules for Copilot. deepsense.ai's strongest advantage: deep ML talent, with evaluation of retrieval quality treated as part of the build.
How do Avanade and deepsense.ai differ in pricing?
Avanade pricing: Enterprise consulting rates, fixed-scope programmes and managed services; rates on request. deepsense.ai pricing: T&M and dedicated teams; rates on request. Neither firm publishes a full rate card; a discovery call is required for project-specific quotes.
Which is better for enterprise: Avanade or deepsense.ai?
deepsense.ai 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 Avanade and deepsense.ai?
Avanade's primary differentiator is: a Microsoft-only practice of about 59,000 people covering Dynamics 365, Azure OpenAI and Copilot governance. deepsense.ai's primary differentiator is: research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets. They also differ in team size (50,000+ vs 101–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Financial services, Retail vs Manufacturing, Retail).
Verify all details directly with each company before making a decision.