DS Stream
Warsaw data and AI engineering firm with a packaged LLMOps setup
What is DS Stream?
DS Stream was founded in Warsaw in 2017 and has between 150 and 200 engineers, with a US entity in Delaware. Its LLMOps offer bundles an evaluation harness, prompt versioning, guardrails, observability, and routing across several model providers. The company says clients see measurable impact in six to ten weeks on AWS, Google Cloud, or Azure (per company website; independently unverifiable). Data engineering is its other main line, which helps when the real blocker is the data feeding the model.
DS Stream works primarily with clients in Retail, Consumer goods, Financial services, Healthcare, Media sectors. Its primary differentiator is: Packaged LLMOps setup with evaluation, prompt versioning, guardrails, and model routing.
DS Stream tech stack and services
| Service area |
|---|
| LLM Gateway & Cost Control |
| Evaluation & Regression Testing |
| Monitoring & Drift Detection |
| Data Engineering |
| MLOps & Model Serving |
DS Stream pricing
Short answer: DS Stream prices its work as follows: project and team pricing; rates on request. Minimum engagement is not publicly disclosed; a discovery call is required.
| Engagement model | Typical range | Best for |
|---|---|---|
| Fixed-scope project | Quoted per project | A well-defined scope |
| Dedicated team | Monthly team rate; not public | Continuing the build after a pilot |
DS Stream pros and cons
| Advantages | Things to consider |
|---|---|
| +LLMOps comes as a defined package, which is easier to scope | -Smaller and younger than most firms on this list |
| +Prompt versioning and guardrails are part of the default setup | -Its six-to-ten-week claim is the company's own |
| +Strong data engineering behind the AI work | -No staged-rollout or managed-run service named |
| +Works across all three major clouds |
DS Stream vs alternatives
How DS Stream compares to the other top AI Implementation providers.
| Company | Best for | Key difference | Rating | Compare |
|---|---|---|---|---|
| Tensorway | Teams whose AI pilot works but can't ship. | Model gateway with routing, provider fallback, and regression tests, released through a canary rollout | 4.8 | Full comparison |
| Provectus | AWS shops taking GenAI pilots to production. | AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker | 4.6 | Full comparison |
| Grid Dynamics | Enterprises moving several AI pilots to production. | Forward-deployed engineers working from ready-made GAIN platforms for agentic and retail AI | 4.5 | Full comparison |
| deepsense.ai | Teams that need measured accuracy before launch. | Evaluation-first engineering that proves accuracy on your data before release | 4.5 | Full comparison |
| Neurons Lab | Banks and insurers shipping AI on AWS. | Financial-services AI built inside existing compliance controls on AWS | 4.4 | Full comparison |
| Datatonic | Google Cloud users needing MLOps and managed run. | Vertex AI MLOps with a managed service to run models after launch | 4.4 | Full comparison |
| Quantiphi | Large document and contact-center AI programs. | Large Google Cloud and AWS engineering bench for document and speech AI in production | 4.3 | Full comparison |
| ML6 | European firms needing EU-compliant production AI. | European AI engineering with EU AI Act and GDPR requirements built into delivery | 4.3 | Full comparison |
| Thoughtworks | Engineering orgs wanting disciplined AI delivery. | Continuous delivery practice applied to models and prompts, with tool views published in its Technology Radar | 4.3 | Full comparison |
| N-iX | Mid-size and large firms wanting nearshore MLOps. | Dedicated MLOps practice backed by a large nearshore engineering bench | 4.2 | Full comparison |
| Addepto | Mid-size firms wanting tested LLM apps cheaply. | Open-source LLM testing (ContextCheck) and a low $10,000+ Clutch entry point | 4.2 | Full comparison |
| RTS Labs | US mid-market firms on a small budget. | The lowest entry point on this page, with a committed ship date for production code | 4.1 | Full comparison |
| EPAM Systems | Enterprises adding AI across many products. | Engineering capacity to put AI into dozens of products under one program | 4.1 | Full comparison |
| Accenture | Multinationals rolling AI out across many countries. | Staffing and compliance depth to run production AI in many countries at once | 4.1 | Full comparison |
| Winder.ai | Teams needing senior MLOps advice and review. | Senior MLOps expertise from a recognized author, at boutique scale | 4.0 | Full comparison |
| NineTwoThree AI Studio | Funded companies launching an AI product. | Product design and engineering together for customer-facing AI launches | 4.0 | Full comparison |
| Globant | US firms wanting nearshore AI engineering. | Nearshore Latin American engineering teams in US time zones | 4.0 | Full comparison |
| SoftServe | Existing clients extending engineering into AI. | Google Cloud Premier engineering firm with an MLOps and generative AI practice | 4.0 | Full comparison |
| Capgemini | European multinationals pairing AI with outsourcing. | Production AI bundled with outsourced business operations after the WNS deal | 3.9 | Full comparison |
| InData Labs | Mid-size firms with one focused AI project. | Discovery, proof of concept, and production build from a small data science team | 3.9 | Full comparison |
| Instinctools | Palantir users building agentic workflows. | Palantir Foundry and AIP implementation alongside custom software engineering | 3.9 | Full comparison |
| Netguru | Product teams adding AI features to apps. | AI features shipped as part of web and mobile product work | 3.9 | Full comparison |
| STX Next | Python teams needing extra AI engineers. | Python engineering depth for AI that lives inside your codebase | 3.9 | Full comparison |
| 10Clouds | Smaller banks and lenders adding AI. | A dedicated financial-institutions AI unit with its own AIConsole platform | 3.8 | Full comparison |
| LeewayHertz | Buyers wanting a platform-based AI build. | Builds on its own ZBrain platform, now backed by The Hackett Group | 3.7 | Full comparison |
DS Stream FAQ
What is DS Stream?
Warsaw data and AI engineering firm with a packaged LLMOps setup
How much does DS Stream charge?
Pricing model: project and team pricing; rates on request. Minimum engagement is not publicly disclosed. A discovery call is required to get project-specific quotes.
What tech stack does DS Stream use?
DS Stream works with AWS, Google Cloud, Azure, Databricks, Kubernetes. Primary industries served include Retail, Consumer goods, Financial services, Healthcare, Media.
Is DS Stream right for enterprise?
Best for: teams wanting packaged LLMOps at nearshore rates. Team size: 150–200. Key consideration: Smaller and younger than most firms on this list.
What are the best DS Stream alternatives?
The best alternatives to DS Stream depend on your use case. Top options are:
- Tensorway: model gateway with routing, provider fallback, and regression tests, released through a canary rollout
- Provectus: AWS Premier Tier MLOps and generative AI engineering on Bedrock and SageMaker
- Grid Dynamics: forward-deployed engineers working from ready-made GAIN platforms for agentic and retail AI
Compare DS Stream with other AI Implementation providers
Verify all details directly with DS Stream before making a decision.