Sprinkling AI here and there? Not our style. We think big and operationalize artificial intelligence across the entire SDLC to speed up the development process and cut its costs for you, all while keeping security, ethics, and compliance front and center.
Why sit on potential when you can turn it into better performance? We use artificial intelligence to cut the dull paperwork across SDLC, so that team members can redirect their efforts to aligning stakeholders, coordinating the dedicated team, preventing scope creep, and driving strategy forward.
| TASK | BEFORE | AFTER | EFFICIENCY GAIN |
| Analyzing gaps in project documentation | 4 hours | 10 minutes | ×24 faster |
| Assembling a project team based on the staff skills and availability | 7 days | 2 days | ×3.5 faster |
| Finding relevant information in documentation | 1 hour | 5 minutes | ×12 faster |
| Creating follow-up tasks | 30 minutes | 5 minutes | ×6 faster |
| Onboarding new team members | 12 hours | 5 hours | ×2.4 faster |
In the pre-GenAI era, it took us up to 8 weeks on average to deliver a lightweight proof of concept. Now, with AI handling the grind, that same time is enough to craft a solid PoC with a prioritized backlog for further MVP development.
From software planning to upkeep, we apply AI with purpose, aiming to automate the repetitive, untangle the complex, and deliver faster without cutting corners on quality or security.
AI takes the daily grind off business analysts’ plate, so they can focus on diving into your business context, aligning stakeholders, and guiding big-picture thinking.
The less time our UX/UI designers spend on repetitive, automatable tasks, the more time they can invest in testing new ideas and refining the user journeys to deliver intuitive, accessible interfaces that win customers from day one. AI supports the design process by:
By 2027, 70%* of professional developers will use AI-powered tools to write code faster. But leading enterprise teams, like Shopify and Amazon, are already there, treating AI as a standard part of their workflow. We do the same, since ignoring AI tools slows down delivery, putting the clients a step behind their competitors. AI assists our development teams by:
* According to Gartner
The tighter your feedback loops, the faster you ship stable, secure, and easy-to-scale software. Our QA engineers reinforce the process by using AI to automate repetitive preparation work.
Our development team is always on the lookout to ensure the software won’t stumble on the finish line, and AI helps them to keep releases smooth and stress-free.
Building software is just the beginning. A well-orchestrated solution upkeep is what matters just as much. Our multi-tier application support teams leverage AI tools to sharpen preventive, reactive, and perfective maintenance.
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You’re not the first to question the trustworthiness, reliability, and quality of AI outputs. We make sure none of your concerns go unanswered. Our team prioritizes responsible AI usage just as much as speed and efficiency.
| Your concern | Our responsible AI framework in action |
| Security breaches | We only use proven tools that guarantee proprietary code stays private and won’t be used to retrain AI models. |
| Copyright violations | All types of data are checked with copyright detection tools before being fed into AI systems. |
| Lack of AI explainability | We adhere to the HELM framework and prioritize the foundational models with the highest scores on the transparency index. We also put a premium on the model and decision lineage to have a detailed audit trail of the model’s decision-making process. |
| Speed over security | We only use AI tools approved by our legal and security teams, and never without your prior consent. Any experimentation with new AI software happens in an isolated sandbox, away from production systems. |
| Inconsistent or biased results | We don’t blindly ship AI outputs. Subject matter expert oversight is mandatory for every line of code, design asset, or spec. |
| Overreliance on AI | AI tools accelerate our work, but they don’t replace human expertise. Instinctools’ specialists polish every result and stay in charge of big-picture decision-making to deliver consistently high software quality. |
| Ambiguous liability | Whether we cooperate with you under a staff augmentation or dedicated team model, our employees are responsible for the outcomes of AI-assisted work. |
| AI compliance risks | Our use of AI tools is aligned with the NIST AI RMF, SOC2 for AI, and EU AI Act by design. We also monitor the AI regulatory landscape to factor in new legislations before they come into force. |
Time is money, and with our approach, you save both. AI handles routine low- and mid-level tasks, such as generating boilerplate code, creating test cases, drafting project documentation and reports, etc. Freed from the grunt work, our cross-functional team can move faster and focus on what matters: oversight, deeper strategic reasoning, and high-value problem solving.
Senior Business Analyst
Drafting high-level acceptance criteria and internal docs like user guidelines now takes half the time. It frees me to focus more on stakeholder alignment and in-depth business context analysis.
Generative and Agentic AI Product Strategist
AI helps me cut time spent on competitive scans, value proposition drafts, and early feature framing by nearly 50%. It’s like having a second brain for the groundwork, so I can focus on shaping the big bets.
Head of Backend Department
Coding has become up to 60% faster with AI. But what really stands out is the 90% automation of documentation updates. That’s the time our engineers now spend building, not writing.
Integration Architect
AI streamlines up to 80% of the integration preparations like schema mapping, connector configs, and boilerplate flows. I’m free to tackle edge cases and system-level design without getting buried in setup work.
Head of QA Department
Our QA engineers now spend 30-40% less time generating testing coverage, so they can focus on edge cases where human control is critical. Plus, with AI-powered defect detection, we’re catching issues in requirements documentation, APIs, and during autonomous visual testing with 10% more accuracy.
Head of UX/UI Department
Mock-up generation used to take hours. Now, with AI-powered tools, our designers are iterating 1.5 times faster.
Lead DevOps Engineer
With AI handling much of the project’s infrastructure monitoring, we’ve shortened deployment cycles by 40% and ship updates quicker without compromising system stability.
Project Manager Officer
AI has trimmed hours off operational activities. Whether it’s drafting a project charter, risk register, or communication plan, we’re completing the tasks up to 90% faster without compromising accuracy.
The expectations for the quality of the initial product were very high. I think *instinctools did a great job ensuring those expectations are met. We met the developers we were going to be working with and it quickly became apparent that they are very qualified and were able to deliver the vision that we had from our side for the product. They clearly told us what they were going to do, and if there were questions or problems along the way, they clarified them really quickly thanks to transparent communication.
We had a tight delivery deadline and *instinctools has been able to find another developer and assign him to our project from one day to another. And we’ve been able to successfully deliver this project. When the partner is good, things are just getting done. And that was the case with *instinctools.
The quality has been good. It’s been on the expected level: things come on time, we have a good visibility on the things that *instinctools developers are doing and performing for us, communication is good. Wherever we see that we need some more exra resources, we have found *instinctools to be a good partner in helping us out on those areas.
I’ve been impressed by the available skillset, the flexibility to ramp up resources quickly, and the scalability to extend development teams on short notice. I look forward to continue collaboration with *instinctools and their contribution to our projects.
People at *instinctools are quite tech heads, which I like. They have used very advanced libraries, advanced techniques, advanced coding paradigms. So the advantage is that we get reusable code, that we get well-testable code, we get well-maintained code.
The *instinctools team exhibits the flexibility and professionality required for young companies. You can rely on their tested structures and processes that integrate nicely with your internal workflows. Being able to grow your team quickly with experienced professionals that start delivering value immediately and without a long interview process is a huge help. And personally, you will be working with a team of kind and interesting people.
The team is dependable when it comes to managing time and finances, consistently staying within the designated budget. We’re pleased with *instinctools. Their business analysts are exceptional. They serve as the spokespeople between technology and business, representing both sides effectively.
Instinctools is good at understanding the technical issues – once an issue is outlined, they do not need repeated explanation. They also do not simply accept a proposed solution, but they think about it and propose a better solution. I was really impressed by the custom interface they built for us – we outlined the requirements, and they implemented them in a user-friendly way that makes the interface a pleasure to use.
Instinctools does deliver on time and budget. The company proactively asks how they can support our efforts and provide ideas how to help us with very good candidates with expertise that either we requested or that instinctools identified to be missing.
The team demonstrated effective project management, timely delivery, and responsiveness to our needs. They established open communication to facilitate ongoing dialogue and held regular sprint meetings to keep stakeholders informed and engaged throughout the development process.
AI tools automate routine tasks across the SDLC, speeding up delivery and freeing business analysts, software developers, UX/UI designers, QA engineers, and project managers to focus on more complex, strategic, high-impact work. That way, you get solid, easy-to-maintain software faster without skimping on data privacy and solution security.
Our hands-on experience indicates that responsible use of AI throughout the SDLC results in a consistent and always up-to-date code base, fewer errors slipping to the pre-deployment stage, and faster incident response, ultimately contributing to getting higher-quality software at a lower cost.
