Tensorway vs deepsense.ai: full comparison for 2026
Quick verdict
Tensorway (4.8/5) edges ahead of deepsense.ai (4.4/5) overall. Tensorway is the better choice for mid-market firms adding AI to existing CRM and ERP. 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.
Tensorway vs deepsense.ai: head-to-head summary
| Criterion | Tensorway | deepsense.ai |
|---|---|---|
| Founded | 2019 | 2014 |
| HQ | Alicante, Spain | Warsaw, Poland |
| Team size | 50+ | 101–200 |
| Rating | 4.8 / 5 | 4.4 / 5 |
| Primary differentiator | Integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call | Research-grade ML engineers who build retrieval systems and evaluate them with measurable accuracy targets |
| Pricing model | Fixed price for the audit and pilot, then dedicated team or managed service; API run cost estimated during the pilot | T&M and dedicated teams; rates on request |
| Min. engagement | Not disclosed | Not disclosed |
| Primary tech stack | Salesforce, HubSpot, Microsoft Dynamics 365 | LangChain, Azure OpenAI, AWS Bedrock |
| Industries served | Legal services, Financial services, Healthcare records, Retail & e-commerce, Private equity | Manufacturing, Retail, Financial services, Healthcare |
Tensorway vs deepsense.ai: overview
Tensorway
Tensorway is an AI-first engineering company founded in 2019 and headquartered in Alicante, Spain, with a team of more than 50. Its integration work runs on top of existing platforms such as Salesforce, HubSpot, Dynamics 365, SAP, Oracle and NetSuite, so clients keep their systems of record and skip a migration. Requests pass through a single gateway that masks personal data before it reaches a model and limits each answer to documents the employee is already allowed to open. For Liner Legal, a U.S. law practice, it cut medical-record processing from roughly a week to 5–15 minutes and automated about four days of manual CRM reconciliation (per company website; independently unverifiable). The delivery leads behind it bring 20-plus years of business-software engineering to the work.
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: Tensorway vs deepsense.ai
| Capability | Tensorway | 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: Tensorway vs deepsense.ai
| Framework / platform | Tensorway | deepsense.ai |
|---|---|---|
| Salesforce | ✓ | N/A |
| SAP | ✓ | N/A |
| Microsoft Dynamics 365 | ✓ | N/A |
| HubSpot | ✓ | N/A |
| Snowflake | ✓ | N/A |
| Databricks | ✓ | N/A |
| Azure OpenAI | N/A | ✓ |
| AWS Bedrock | N/A | ✓ |
| LangChain | N/A | ✓ |
| ServiceNow | N/A | N/A |
Pricing comparison: Tensorway vs deepsense.ai
| Criterion | Tensorway | deepsense.ai |
|---|---|---|
| Minimum engagement | Not disclosed | Not disclosed |
| Engagement models | Fixed-scope audit or pilot, Dedicated team, Managed services | Time & materials, Dedicated team |
| Rate transparency | Not public | Not public |
| Price tier | Mid-market | Mid-market |
Target audience comparison: Tensorway vs deepsense.ai
| Dimension | Tensorway | deepsense.ai |
|---|---|---|
| Best company size | Startup to mid-market | Startup to mid-market |
| Best industries | Legal services, Financial services, Healthcare records | Manufacturing, Retail, Financial services |
| Best use cases | Reconciling CRM records against case or order data that staff currently match by hand., Extracting and cross-checking fields from medical records, invoices or contracts, then routing them into the ERP. | Retrieval assistants over technical manuals or internal knowledge bases., Visual defect detection on production lines with edge inference. |
| Typical project type | Fixed-scope audit or pilot | Time & materials |
Tensorway vs deepsense.ai: pros and cons
| Tensorway | |
|---|---|
| + | Works against the systems you already own, and where a platform has no usable API it reads from database replicas, message queues or file exports |
| + | Personal data is masked before a prompt leaves your perimeter, and answers respect the same document permissions the employee has today |
| + | A one-week system audit produces an integration plan and ROI estimate before any build money is committed |
| + | The first workflow goes live on real data in 2–4 weeks and is measured against the baseline taken during the audit |
| + | One gateway logs every request, enforces rate limits and tracks token spend per feature, which makes the monthly AI bill explainable |
| - | No prices are published, so you only see a number after the scoping call |
| - | A team of 50+ has no round-the-clock global delivery footprint like the large integrators |
| - | Its pages list no certifications and no named partner tier with an LLM provider or hyperscaler |
| 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 Tensorway?
A typical fit: reconciling CRM records against case or order data that staff currently match by hand.
Integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call. Minimum engagement is not publicly disclosed. Works best with clients in Legal services, Financial services, Healthcare records, Retail & e-commerce, Private equity.
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: Tensorway vs deepsense.ai
| Your situation | Recommended choice |
|---|---|
| You want a fixed-price audit or pilot before committing | Tensorway |
| AI has to work inside your existing CRM or ERP | Tensorway |
| Personal data must be masked and answers limited by user permissions | Tensorway |
| Your budget is at the lower end | Compare: Tensorway (Not disclosed) vs deepsense.ai (Not disclosed) |
| You want the vendor to run the AI service after launch | Tensorway |
| You are building multi-step agents across systems | deepsense.ai |
Use case fit: Tensorway vs deepsense.ai
| Use case | Tensorway fit | deepsense.ai fit | Winner |
|---|---|---|---|
| Reconciling CRM records against case or order data that staff currently match by hand. | Strong | Limited | Tensorway |
| Extracting and cross-checking fields from medical records, invoices or contracts, then routing them into the ERP. | Strong | Limited | Tensorway |
| 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: Tensorway vs deepsense.ai
Tensorway (4.8/5) is the stronger overall choice for most AI Integration projects. Integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call.
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
Tensorway vs deepsense.ai FAQ
Is Tensorway better than deepsense.ai?
Tensorway (4.8/5) scores higher overall, but "better" depends on your use case. Tensorway's strongest advantage: works against the systems you already own, and where a platform has no usable API it reads from database replicas, message queues or file exports. deepsense.ai's strongest advantage: deep ML talent, with evaluation of retrieval quality treated as part of the build.
How do Tensorway and deepsense.ai differ in pricing?
Tensorway pricing: Fixed price for the audit and pilot, then dedicated team or managed service; API run cost estimated during the pilot. 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: Tensorway 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 Tensorway and deepsense.ai?
Tensorway's primary differentiator is: integrates with the CRM and ERP you already run, with PII redaction and per-user access rules applied before any model call. 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+ vs 101–200), minimum engagement (Not disclosed vs Not disclosed), and primary industries served (Legal services, Financial services vs Manufacturing, Retail).
Verify all details directly with each company before making a decision.