A product studio bringing
an owner’s perspective
Outsourcing
company
You bring the requirements. They implement
Traditional outsourcing works best when you already know what you want to build. You bring the product vision, requirements, and priorities. The team turns them into a working set of features. Their primary responsibility is delivery: providing the engineering expertise and capacity to complete the agreed work on time and within budget.
01 Product
studio
You get a technology partner focused on product-market fit
・Product strategy and launch experience.
・Deep business analysis and technical feasibility.
・Business vision translated into future-proof specs.
・Realistic development and launch planning.
・Process built around smart use of resources.
・Responsibility for product outcomes and quality. 02
What it means to think like a product owner?
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We work as one team with you
Your goals and quality metrics become shared targets. Our process adapts to your project, not the other way around. We shift the focus from completing tasks to delivering outcomes.
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Business context comes first
Before development starts, we clarify your business goals and analyze workflows and risks. Our Product Owner, Designer, and Tech Lead turn this into a technical specification and a realistic development roadmap.
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Your product's value is our North Star
We look beyond development to your value proposition and user experience, bringing our strategic product vision where needed. We develop iteratively, using market feedback to guide the product toward PMF at lower cost.
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With the product's future in mind
We design your architecture around how the product needs to evolve and scale. Environments, deployment, security, and operational standards are defined from the start, with production-ready infrastructure and CI/CD in place.
Our AI lab becomes your accelerator
Voice Automation
Runs an entire outbound call from dialing through the phone menu, the hold queue, and the conversation itself, returning the answer as structured data your systems can act on.
Chat Automation
Carries a conversation to a defined result across menus and free text, tracking what has actually been collected outside the model so the output is a verified record rather than a transcript.
Prospect Scoring & Outreach
Ranks prospects on fit signals and sends the first touch automatically, so sales time lands on the accounts most likely to close.
Lead Intake & Qualification
Captures every inbound lead, asks the qualifying questions, and routes it to the right owner within minutes of arrival.
Document (Report/CV) Evaluation
Reads incoming documents against your criteria and returns a structured verdict with the supporting evidence, replacing hours of manual screening.
Web Portal Automation
Logs into third-party portals and completes lookups and submissions on your behalf, covering the systems that expose no API.
Interactive Q&A for Course Promotion
Answers prospective student questions about a course in real time, converting interest into enrollment while attention is still there.
FAX, SMS, Email Automation
Handles legacy channels, parsing what arrives and dispatching what goes out, so nothing sits unnoticed in an inbox or on a fax tray.
Data Normalization
Converts records from every source into one consistent schema, so downstream agents and reports stop breaking on format mismatches.
Data Cleansing and Enrichment
Clears duplicates and errors out of your records and fills missing fields from external sources, so decisions run on data your team can trust.
Human-in-the-Loop Review
Sends low-confidence outputs to a person for approval before they take effect, so high-stakes workflows can be automated with control retained.
Source-Grounded Output
Ties every answer to the source document it came from, so your team verifies a result in seconds.
IVR Navigation
Reads payer prompts as they arrive, enters identifiers in whatever format each payer asks for, and stays on the line through queues, so calls reach a live representative with no one waiting on hold.
Sensitive Data / PHI Anonymization
Detects and masks PHI and other sensitive fields before data reaches a model or a log, so real records can be used in AI workflows without expanding compliance exposure.
Verification of Insurance Benefits
Pulls a patient's benefit details ahead of the visit, so coverage limits and patient responsibility are known before service is delivered.
Eligibility Verification
Re-checks coverage ahead of each appointment and flags the visits that would be denied, so the front desk fixes them before the patient arrives.
Prior Authorization
Assembles authorization requests, submits them, and tracks each one to a decision, removing the daily phone-and-portal work that delays care.
Claim Automation
Builds and submits claims with payer-specific checks that catch denial-causing errors before the claim leaves your system.
Build on our product expertise
Tap into the launch expertise, R&D laboratory, and pre-built AI components behind our own products to empower yours.
Get in touch
Use resources smarter with Agentic Engineering
up to 3-4× faster
Product, requirements, design, coding, QA, and DevOps agents work alongside senior engineers, compressing work across every stage of delivery.
50-75% lower costs
Smaller senior teams build and run products while AI automates repetitive development, testing, monitoring, troubleshooting, and ongoing maintenance.
Quality under control
Senior engineers own architecture, business logic, security, and releases, while automated reviews, tests, and quality gates verify AI-generated work
How our AI SDLC protects quality at speed
Catching mistakes while they’re still cheap
Keeping human review at AI speed
Verifying what AI actually did
Moving fast without letting errors move faster
Different approaches for different needs
Lean team
+ AI
When time-to-market is critical, you get a production-ready system, delivered up to 75% faster with a team of one Solution Architect and a (part-time) Proxy Product Owner.
01 Cross functional
AI pods
For complex software, we provide a full-fledged team. We tailor the exact roles to each project, including AI Developers, QA, DevOps, Data Engineers, PM/Delivery Managers, Product Owner, Designers, and Tech Leads.
02You get the same Senior engineers in both approaches, just faster with AI.
Predictable and transparent process
Product discovery
- AI accelerates: meeting capture, requirements structuring, market and competitor research.
- Humans own: scope decisions, risk assessment, and the trade-offs behind them.
- What you get: technical understanding of how to achieve the business goals, early visibility into risks and dependencies.
Design and setup
- AI accelerates: environment scaffolding, CI/CD boilerplate, baseline security config.
- Humans own: architecture, deployment model, and security baseline decisions.
- What you get: production-ready infrastructure and CI/CD, reliability and security controls from the start.
Iterative development
- AI accelerates: boilerplate code, first-draft tests, documentation updates, log analysis, first-pass debugging.
- Humans own: engineering judgment, code review, quality gates on every change.
- What you get: new features delivered in small, reviewable increments.
Testing and go-live preparation
- AI accelerates: UAT and BDD scenarios, end-to-end tests, release notes.
- Humans own: production readiness, edge cases, integrations.
- What you get: release readiness backed by coverage of real user journeys and fewer regressions
Support & improvement
- AI accelerates: monitoring, anomaly detection, incident analysis, backlog refinement.
- Humans own: prioritizing fixes and planning iterations from usage data.
- What you get: fast response to issues and post-launch work driven by real usage.
What
our
clients
say
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Alexander Radchenko
CEO, Radenia AG,
SwitzerlandTransparency and focus
on business value«I've been working with multiple IT services providers for more than two decades and what sets MindK team apart is transparency, focus on business value and quality of the services provided.»
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Emilie Lindqvist
CEO, Juvo,
NorwayAdmirable degree
of involvement«MindK consistently shows a degree of involvement in the project that is admirable. We all feel like one team.»
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Allison Erickson
Director of Product, The Lactation Network
USA Such quality work in such efficient timing
«I have nothing but great things to say about our partnership with MindK and the solid work they have done and continue to do for the growth of our company. Our rapport is strong which is a reflection of their professionalism, hard work, and great outputs.»
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Philip Yancey
Partner at Converze Media,
USA A reliable partner
«I appreciate how MindK was able to build such a platform from conference calls, emails and basically a wish list of what our company wanted and needed automated to make Converze a more efficient and effective player in our space.»
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Jens Christian Bang
CEO, Already On
Norway MindK always finds a solution
«We've been successfully cooperating with MindK since 2010. What we were impressed with about people at MindK during all years of partnership — they never give up. We're not worried, as we know that MindK always finds a solution.»
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Zaheer Mohiuddin
Co-Founder, Levels.fyi
USA This isn't your typical outsourcing shop
«The quality of work and the interactions with the team felt akin to anyone that I've worked within the Bay Area in technology. MindK's expertise is for real and the bar is high. This isn't your typical outsourcing shop, MindK has top-notch engineers and PMs.»
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Mark Lange
CMO, Reputation.com
USA A client-first approach
shop«It's been refreshing to work with a team that puts us as a client first no matter the circumstances and goes out of their way to ensure that our needs are not only met but exceeded. I have no reservations in recommending MindK to any business looking for a top-tier team.»
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Jesse Raccio
CTO, The Game Band
USA The team is always there to dig in and help
«I’m happy with MindK’s agility, which relates to their communication. If we need to pivot on something, they’re ready to go in a different direction, and it doesn’t take a lot of energy to move that ship. The team is always there to dig in and help us out when we need to understand anything. Overall, they’re really supportive.»
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Jason Lutton
CEO, International Surrogacy Center
Impressed with their ability to understand our industry
«MindK reduced the time a surrogate takes to complete an online application, increased the number of completed applications, and streamlined our intake process, resulting in fewer staff man hours needed to complete the backend processes for finalizing an applicant.»
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Jordan Crone
Chief Experience Officer, Melody
USA Smooth
communication flow«Our project has been going smoother than I could have imagined... It's the first time I've worked with a dev team a distance away that didn't have major (or any, for that matter) hiccups or have things lost in communication. I wish we could snatch them and make them a part of our team.»
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Al Hariri
Co-Founder, Vitagene
USA Results-oriented and
outcome-driven«I can tell you confidently that they are different from your regular agency that just wants to charge as much money for their work as they can get away with. MindK is completely results-oriented and outcome-driven.»
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Riccardo Pessina
Head of Operations, Bitrock Srl
Italy One of the best partners we had
«MindK has collaborated with us in supporting the final client in a project regarding DevOps activity. MindK is one of the best in terms of quality of profile proposed and time to market. The feedback we receive form the final client is excellent.»
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Per Otto Larsen
Head of CSR Services, CEMAsys.com
Norway High level of detail
and thoughtfulness«The level of detail and thoughtfulness of what they deliver is so good, that a simple explanation of the next idea serves as the basis for them to take it and turn into reality. MindK’s support allows us to focus on core business, product growth and our customers’ needs.»
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Ida Groth
Senior Product Manager, Building Materials Company
Norway Responsibility
and proactiveness«It’s so comforting to know that they see the whole picture and take full responsibility. It’s made all of the difference. I was most impressed with their proactiveness.»
Let's work together
Let us know about your technology challenges and we'll contact you
within 24 hours to schedule a free strategy session.
FAQ
- What are the core values driving your collaboration with a client?
The interests of the client always come first. The highest value for the team is the usefulness of the product, its market relevance, and its ability to satisfy the client. We work not as “doers”, but as a product team that helps to form a value proposition, understand which components or features will bring the highest value to the market, and determine what should go into the MVPю
We always look at the product through the prism of the real end-user needs, market situation, competitors, and the client’s business goals. For some clients, time-to-market is critical. In this case, we focus on highlighting the most valuable part of the product, quickly launching the MVP, and only then expanding the product. This reduces risks and investments in the early stages.
If the client needs the 1.0 release to be a feature-rich system, we build a complete roadmap, segment features, assess technical dependencies, and create a backlog with release phasing.
A client doesn’t have to know all aspects of the market or technology. A Discovery phase helps in refining the business idea, forming a value prop, assessing the cost and risk. No one knows the product better than end users. That’s why we always advise: go to market early, collect real feedback, test hypotheses, pivot if necessary.
We explain risks and restrictions, offer alternatives, suggest optimal solutions, and help the client understand the picture “beyond the framework” of his initial idea.
- Do you use any classical approaches to software development or their modifications?
MindK follows the principles of the Scrum Framework, the most popular and effective methodology for managing complex products and IT projects. Here’s how we adapt this framework to meet the client’s needs:
Time-boxing. We work in sprints and adhere to a clear structure (planning → development → testing → demonstration → retrospective). The exact duration of the sprint depends on the client. 1–2 week sprints work when the product is early and requires quick solutions. For products with complex business logic or integrations, we recommend 2–4 week sprints
Transparency. We provide transparent reports, artifacts, team capacity, regular meetings and reviews, as well as data on progress, risks, and blockers. This creates conditions for the client to make informed decisions.
Adaptability. The team constantly validates requirements with the client. We adjust the approach in response to new data and user feedback.
Definition of Ready (DoR) and Definition of Done (DoD). We use classic DoR/DoD concepts that require the inclusion of QA at early stages, taking into account non-functional requirements, clear acceptance and testing criteria, as well as regular refinement before planning. This reduces the risks of overestimation and underestimation.
Collaboration with the client as one team. MindK practices joint working groups, regular discussions of priorities, and client involvement at all stages. This allows you to make decisions quickly and confidently.
The Client First principle. All our Scrum adaptations serve this one key principle. This means we select optimal processes instead of imposing one standard for everyone. We adapt sprints, rituals, and communication to the style and rhythm of the client. The team focuses on the result, not on the formal observance of rituals. This way, we maintain the discipline of the process and flexibility in its implementation.
- How do you reduce uncertainty inherent ot software projects?
Discovery Phase: initial product analysis, vision formation, hypothesis testing and definition of project boundaries.
Impact Mapping: processing of business goals, user scenarios, and system logic.
Backlog Refinement: regular refinement, decomposition, and prioritization of backlog elements.
Definition of Ready (DoR): criteria for readiness of a task for development, which reduce the risk of uncertainty in the sprint.
User Stories & Use Cases: description of functionality through the eyes of the user for a better understanding of the logic.
Acceptance Criteria (AC): detailed acceptance conditions, including edge cases and non-obvious scenarios.
Prototyping: rapid visualization of interfaces, which helps to agree on the logic for development.
Spikes: short technical studies to check technological risks or complex integrations.
Technical Clarification Sessions: clarifying technical sinks with the team to identify dependencies and risks.
Dependency & Impact Analysis: understanding the impact of tasks on each other to avoid hidden blockers.
AI-Assisted Analysis: identifying gaps in requirements to generate solution options and a preliminary structure of tasks.
Integration & Technical Contracts: preparing specifications and technical agreements before implementation.
Client Sync Meetings: communicating regularly to get answers to open questions and quickly clarify requirements.
- How exactly do you use AI at each stage of the SDLC?
Ideation and discovery: AI captures workshops, produces transcripts, extracts action items and requirements, scans market and regulatory sources, and drafts process maps. Humans still define requirements, decide what matters, and validate outcomes.
Requirements gathering: AI drafts refinement-ready stories, acceptance criteria, and edge cases. The Proxy Product Owner is responsible for prioritization, scope, and ambiguity removal.
Design: AI accelerates UI exploration and visual alternatives. Designers remain responsible for UX quality, accessibility, hierarchy, and product fit.
Development: AI generates boilerplate and patterned implementation, especially DTOs, services, and other code that fits the “Golden Repository,” and helps debug using logs and runtime context. Developers keep ownership of business logic and final code quality.
Testing: AI generates unit and integration tests, mocks, BDD/UAT scenarios, and self-healing UI/E2E automation through Testsigma. QA still decides whether coverage is meaningful and whether the release is safe.
Releases: AI drafts release notes from Git plus Jira/Confluence context, helps prepare demos, and seeds realistic data for sprint reviews. Humans still decide release readiness.
Support and operations: AI assists with monitoring, anomaly detection, and root-cause support through Datadog AI, New Relic AIOps, CloudWatch, and X-Ray.
- What components of code are generated by AI? How do you detect hallucinations and technical errors?
AI helps us generate Terraform, CI/CD scripts, feature scaffolding, DTOs, services, tests, mocks, inline comments, Swagger/OpenAPI definitions, architectural diagrams, release notes, and other technical artifacts.
We control hallucinations by grounding AI in the Golden Repository, existing modules, contracts, namespaces, architecture guidance, runtime diagnostics, and CI/CD gates. Human engineers still validate the result.
AI-generated code is treated as an untrusted first draft. It is reviewed for package validity, dependency provenance, auth and authz flaws, secrets leakage, insecure output handling, missing validation, error handling, test adequacy, and architecture drift.
- What quality standards do you use?
Architectural Standards and Quality. We use architecture with a clear separation of logic (DTOs, Services, Controllers). The code is modular and easily extensible. Following the SOLID principles, AI checks the code for compliance with object-oriented programming. MindK uses the OpenAPI/Swagger standard to generate documentation-as-code, so it never becomes outdated. With self-healing code, our tools analyze logs at runtime and suggest fixes that correspond to the architecture, reducing MTTR (Mean Time to Resolution) by 50%.
Security and Compliance. We use Zero Trust Architecture with the principles of least privilege. Tools like Snyk Code and Amazon Inspector scan code and infrastructure for OWASP Top 10 vulnerabilities in real time. Our infrastructure complies with the CIS AWS Foundations Benchmark by default. Upon request, we can implement GDPR, HIPAA and SOC 2 compliance.
QA & Testing. MindK aims for test coverage of 90%+: AI generates Unit and Integration tests for each new method. Shift-Left testing starts from the moment the first line of code is written. According to our BDD (Behavior-Driven Development) approach, AI translates User Stories into automatic test scripts. MindK uses Testsigma for self-healing E2E tests. If the button ID on the frontend changes, the test does not fail, ensuring the stability of UI checks.
DevOps & Infrastructure. High Availability (HA) with possible Multi-AZ setups (distribution of servers across different availability zones). Auto-scaling groups are configured by AI by default. We implement monitoring standards through Datadog/New Relic with AI-predicted incidents. The problem is surfaced before it affects the user.
- How do you ensure the security of confidential code and data on AI platforms?
All products are architected around the principle of least privilege, encryption at rest, firewalling, zero-trust style controls, vulnerability scanning, environment hardening, and monitoring.
For projects with high security requirements, such as healthcare, we use enterprise-only AI endpoints, strict repository and workspace scoping, automated secret and PHI redaction before prompting, logging, and approval boundaries for AI tools. Minsk also proposes no-training and retention-limited vendor terms together with BAAs wherever a provider may create, receive, maintain, or transmit ePHI.
- How do you ensure reliability and performance in production?
We use an SRE (Site Reliability Engineering) approach, enhanced by Artificial Intelligence. With predictive monitoring, AI sees anomalies before they become failures.
We connect tools, such as Datadog AI, New Relic Applied Intelligence, AWS CloudWatch Anomaly Detection, that learn from system behavior. They know that 80% CPU utilization on Black Friday is the norm, and on Tuesday night is an anomaly.
With auto-scaling, the system itself adds servers when loaded and removes them when they are not needed (saving money). If a component fails, a self-healing system automatically restarts it without the involvement of engineers.
We constantly scan the code for bottlenecks to make the application run as fast as possible.
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