From custom LLM integrations to intelligent process automation - we build AI solutions that create measurable value.
While many companies are eager to explore the potential of AI, few manage to move beyond experimentation and achieve meaningful results. We help bridge that gap by focusing on practical, outcome-driven applications of AI – tailored to your business context.
“Our QA process is too manual and breaks easily - we can’t release quickly with confidence.”
“We're overwhelmed with support tickets and can’t scale fast enough without hiring more people.”
“Our CRM outreach is generic and underperforms - we need more personalized messaging.”
“We generate tons of internal documents, but no one can find or summarize them efficiently.”
“We want to use GPT or Claude in our tools, but don’t know how to embed them properly.”
We turn fragile, manual QA into stable, AI-powered testing pipelines.
We transform overloaded support channels into scalable AI assistants and smart knowledge bases.
We embed LLMs into sales workflows to automate personalized outreach at scale.
We convert static documents and training content into searchable, intelligent knowledge systems.
We translate vague AI ideas into validated, production-ready solutions that deliver real value.
We develop custom AI solutions that are practical, scalable, and deeply integrated into your business workflows. Our expertise spans a wide range of areas – from intelligent agents to AI-powered QA automation and predictive analytics.
Conversational AI tailored to your business. Chatbots, voice assistants, and smart digital agents integrated with CRM, B2B platforms, and customer-facing systems - delivering real-time support and enhancing user engagement.
Boost productivity with embedded large language models. We integrate GPT, Claude, Mistral, and other LLMs into your existing workflows to automate repetitive tasks, summarize content, enhance communication, and power internal tools.
Smarter quality assurance through automation. We build solutions for visual validation, dynamic test generation, and adaptive test execution - reducing manual effort and increasing reliability in complex test environments.
Transform passive documentation into intelligent systems. We turn long-form manuals and training videos into searchable, interactive knowledge bases - enabling contextual help, instant answers, and faster onboarding.
We apply machine learning techniques to identify behavioral patterns, forecast trends, and surface hidden insights - transforming your data into business value.
Empower automation and testing with visual intelligence. We use image recognition, object detection, and OCR to enable smart UI testing, automate workflows for native applications, and extract structured data from visuals and documents.
Deliver natural, hands-free user experiences. We integrate real-time speech-to-text and natural language understanding to build voice-enabled mobile apps, digital assistants, and accessibility features for multi-device platforms.
Validate ideas faster with AI-assisted development. We use tools like Replit, Claude, and Cursor to rapidly build interactive prototypes and MVPs — helping you gather feedback, test assumptions, and iterate quickly without full-scale engineering resources.
Build the backbone of scalable, reliable AI systems. From context-aware knowledge graphs and MLOps pipelines to robust deployment workflows — we develop internal systems that ensure your AI is production-ready, maintainable, and future-proof.
We don’t just build AI – we embed it into real workflows across domains where it creates the most impact.
Customer Support & Onboarding
AI assistants, video parsing, contextual help.
Sales & Personalization
AI agents, lead engagement, CRM automation
Software Testing & QA
Smart UI Testing, test case generation
Business Operations
Workflow automation, log analysis, decision-making
Research & Strategy
AI agents for market scanning, investment validation
B2B SaaS & Enterprise Software
Onboarding tools, predictive insights, support bots
E-commerce & B2B Marketplaces
Intelligent product discovery, sales agents
Healthcare & Wellness
Voice interfaces, accessibility enhancement
Fintech & Investment
Risk assessment, forecasting tools
DevOps & Testing
Automation platforms, intelligent validation
AI Startups / Founders
Rapid prototyping, custom infra for LLM agents
We helped a B2B sales team adopt AI personalization and hyper personalization by integrating large language models (LLMs) into their existing CRM. Our AI email assistant enabled automated prospecting and AI email generation, producing highly tailored messages based on each lead’s profile, industry, sales stage, and real-time CRM data.
By embedding LLM integration directly into the client’s CRM and communication tools, we introduced intelligent content suggestions and AI sales tools that aligned with the brand voice while adapting to varied buyer personas. This AI for B2B solution streamlined manual communication tasks, improved outbound messaging, and saved significant time for the sales team.
Key Results:
Seamless LLM integration with existing CRM and B2B sales automation tools
Smart, automated generation of personalized emails and messages based on real-time CRM data
Streamlined manual workflows and improved team efficiency through AI workflow automation
Higher engagement, response, and conversion rates through AI-assisted outreach
Our expertise with AI sales tools and large language models allows us to build domain-specific research agents that power strategic growth through faster, smarter decisions.
We conducted R&D and implemented AI-driven solutions to help a client modernize their QA strategy and reduce the manual effort involved in test case creation. Using intelligent document parsers and LLM-based tools, we automated the extraction of technical documentation—such as requirements and specifications—to enable scalable, high-quality AI test generation.
By integrating AI for QA and intelligent parsing capabilities into the client’s test automation workflows, we streamlined manual test design, improved test coverage consistency and traceability, and ensured long-term maintainability of the testing pipeline. This innovation accelerated delivery cycles and increased the scalability of QA processes.
Key Results:
Researched and deployed LLM-powered tools and intelligent document parsers
Automated generation of tests and complex test scenarios from source documentation
Improved consistency, traceability, and maintainability in test case design
Reduced manual workload and accelerated QA workflows with AI-driven automation
Our expertise in AI document parsing and LLM integration allows us to build sustainable, high-impact test automation solutions—reducing time-to-market and transforming traditional QA into a data-driven, scalable practice.
For a localization services provider, we developed and deployed multiple AI agents tailored to automate customer research, competitive intelligence, and business opportunity discovery. These agents leveraged LLM integration to gather, process, and synthesize data from diverse sources, turning unstructured information into actionable insights for the business development and sales teams.
By automating proactive lead identification, AI-driven competitive analysis, and market trend tracking, the solution significantly accelerated decision-making, enhanced targeting precision, and supported strategic expansion efforts. AI workflow automation tools minimized manual research and unlocked hidden value across data channels.
Key Results:
Custom AI agents designed for market research, insight extraction, and opportunity discovery
Automated detection of leads, emerging trends, and competitive activity across diverse sources
Structured insights enabling data-driven B2B sales and business development strategies
Accelerated decision-making and reduced manual effort through intelligent research automation
Our expertise with AI sales tools and large language models allows us to build domain-specific research agents that power strategic growth through faster, smarter decisions.
We helped an investment fund validate an AI-powered application by conducting a comprehensive assessment of its market readiness, technical feasibility, and business value. Our evaluation included in-depth MVP validation, market fit analysis, and AI benchmarking to determine the solution’s performance, scalability, and practical applicability across industry-specific use cases.
Leveraging our expertise in AI for investors, we provided a clear, data-driven analysis of the application’s value proposition. This included competitor benchmarking, operational risk identification, and validation of integration potential within existing business processes—delivering the insights needed to support confident, strategic investment decisions.
Key Results:
Assessed technical feasibility, efficiency, and real-world applicability of the AI solution
Conducted MVP and pre-market validation with actionable insights
Performed competitive analysis and benchmarking against market alternatives
Identified operational risks and evaluated integration with current business workflows
Enabled informed investment decisions through expert AI advisory
Our proven methodology supports investors and tech leaders in validating AI solutions early, reducing uncertainty, and aligning innovation with real market demand.
We developed a proprietary UI test automation platform built on the innovative Smart UI Testing approach—an advanced method that combines intelligent pattern recognition, visual validation, and AI-driven workflows to enhance the speed, accuracy, and maintainability of UI testing.
The solution reduces reliance on fragile, script-heavy automation by leveraging artificial intelligence to detect UI changes, validate expected behavior, and adapt test scenarios dynamically. It empowers QA teams to accelerate feedback loops, reduce false positives, and scale automated testing across complex applications with minimal maintenance overhead.
Key Results:
Built a proprietary platform using Smart UI Testing methodology and AI-based validation
Applied LLMs and visual recognition to enable adaptive, resilient UI testing
Reduced false positives and maintenance effort through intelligent test generation
Enabled stable, scalable regression testing across evolving interfaces
Our ability to productize advanced AI testing approaches - such as Smart UI Testing - demonstrates our commitment to solving real QA challenges with scalable, next-generation solutions that support continuous delivery and long-term software quality.
We developed an AI onboarding and support platform to streamline training for users of a complex sales ordering system. By converting long-form training videos into a searchable, AI-powered knowledge base, the solution enables fast, intuitive learning through self service onboarding tools.
Using advanced AI video analysis, the platform automatically parses hours of training content, linking user queries to precise video segments or generating contextual written answers. Combined with screen sharing and natural language input, this intelligent system significantly reduces onboarding time and improves user independence.
Key Results:
Built an interactive AI onboarding tool from existing video materials
Leveraged AI video analysis for content indexing and contextual response
Delivered real-time answers through an AI-powered knowledge base
Enabled early detection of trends, anomalies, and customer behavior shifts
Enabled self service onboarding with minimal support team involvement
Improved user engagement and reduced training costs for complex products
Our expertise in AI onboarding solutions empowers businesses to scale user education and support - efficiently, accurately, and without growing support headcount.
Faced with large volumes of behavioral and operational data, our client initially planned to invest heavily in traditional statistical modeling and programming to extract actionable forecasts. Instead, we proposed a more efficient approach using large language models (LLMs) optimized for time series analysis and customer behavior prediction.
By combining domain-specific historical data with the reasoning and pattern recognition capabilities of LLMs, we enabled predictive insights without the overhead of building custom models from scratch. This significantly reduced development complexity, accelerated experimentation, and delivered high-value forecasts to support agile product and business decision-making.
Key Results:
Applied LLM-powered methods to time series forecasting and behavioral modeling
Eliminated need for custom statistical modeling and reduced implementation overhead
Accelerated insight generation from complex historical and operational datasets
Enabled early detection of trends, anomalies, and customer behavior shifts
Delivered high-value, scalable forecasts for data-driven business strategy
Our expertise in applying LLMs to time-dependent data helps clients unlock the full predictive potential of their datasets - delivering faster, more flexible insights than traditional modeling approaches.
We integrated AI-powered voice recognition and speech-to-text capabilities into lifestyle and wellness mobile apps to enable intuitive, hands-free user interaction. By combining real-time speech-to-text AI with Natural Language Understanding (NLU), we created a smart voice interface that not only transcribes input but also processes and applies it within the app’s workflows.
This approach reduced manual input, streamlined task execution, and provided a more natural, conversational interaction model—especially valuable for on-the-go users, individuals with accessibility needs, and other diverse user segments.
Key Results:
Integrated speech-to-text AI and NLU for real-time voice recognition and intent processing
Enabled voice as a primary input method to reduce friction and enhance usability
Applied voice AI to handle multilingual input and noisy environments
Improved accessibility and engagement through intelligent, workflow-aware interaction
Empowered diverse user groups with a responsive and user-centric experience
Our expertise in voice AI and conversational interfaces allows us to build mobile apps that align with modern user behavior - blending convenience, accessibility, and intelligence in every interaction.
We enhanced a B2B e-commerce platform by integrating intelligent AI agents that deliver hyper-personalized, real-time support throughout the customer journey. Instead of relying on generic automation, we built a tailored personalization engine using CRM data, behavioral history, and LLM integration to create context-aware recommendations, order support, and conversational responses.
Built with n8n.io as part of the automation layer, the AI agent was deeply embedded into the business workflow—not just the UI. Its personality was modeled using real communication history, FAQs, and customer service tone, transforming it into a human-like digital rep that understands customer context and speaks in the brand’s voice.
The agent accesses live CRM data, purchase history, and product inventory to proactively assist with product questions, suggest relevant items, and guide users through complex B2B ordering workflows—boosting engagement while reducing support workload.
Key Results:
Embedded AI agents into the B2B e-commerce and operational workflows
Delivered contextual product recommendations and order assistance
Modeled agent personality using real support interactions and FAQs
Reduced manual support through conversational commerce and AI automation
Enabled proactive support for complex B2B order flows
Enhanced user experience with natural, human-like AI assistants
Our expertise in combining AI, workflow automation, and behavioral data allows us to build intelligent, branded assistants that act as real digital sales reps - scaling e-commerce personalization without sacrificing the human touch.
We helped an early-stage startup accelerate product validation through AI prototyping and low-code development. By leveraging platforms like Replit, Claude, and Cursor, we rapidly built interactive MVPs using no-code tools—enabling fast iteration, early user testing, and compelling demos for investors.
This AI-assisted approach allowed the team to focus on core functionality and user experience, while reducing development time and avoiding the need for a fully staffed engineering team. As a result, the startup was able to demonstrate product viability, test assumptions, and move faster toward funding and market readiness with minimal risk.
Key Results:
Embedded AI agents into the B2B e-commerce and operational workflows
Applied AI prototyping for rapid MVP creation
Used low-code tools to accelerate product development
Enabled no-code iterations without a full dev team
Delivered investor-ready demos to validate product potential
Collected real-time feedback for agile refinement and validation
Our AI-driven prototyping strategy empowers startups to build, test, and iterate with speed and confidence - turning early concepts into validated products without traditional engineering overhead.
We partnered with a California-based AI startup to develop foundational infrastructure for the future of personal AI - enabling autonomous agents to collaborate through shared memory and human-centered context. At the heart of this platform is the Model Context Protocol (MCP): a centralized insight and memory repository that powers seamless interoperability across a multi-agent system.
This user-centric knowledge graph stores structured preferences, behaviors, and real-world insights (e.g., “the user prefers pepperoni pizza”) - allowing AI agents to access and apply shared context in real time. As a result, agents can deliver adaptive communication, intelligent coordination, and hyper-personalized experiences across tools, platforms, and moments.
Key Results:
Embedded AI agents into the B2B e-commerce and operational workflows
Built infrastructure for shared memory across intelligent AI agents
Used low-code tools to accelerate product development
Developed the MCP protocol to unify context and insights across platforms
Created a dynamic, user-centered knowledge graph for personalization and continuity
Enabled seamless agent interoperability with real-time context exchange
Laid the foundation for scalable, interoperable AI ecosystems and long-term orchestration
Our deep experience in AI infrastructure and orchestration positions us at the forefront of next-generation agentic systems - where personalized intelligence becomes both continuous and collaborative.
To automate testing for a complex native desktop application with a non-standard UI, we implemented a custom solution combining computer vision and AI-assisted QA tools. Traditional, DOM-based automation frameworks proved ineffective due to the application’s custom architecture - so we turned to image recognition and OCR to build a more resilient and adaptive testing approach.
Using tools like Tesseract (OCR), SikuliX (image matching), and pyWinAuto (Windows UI automation), we developed a tailored test automation framework that visually identifies and interacts with UI elements - remaining stable even with frequent UI layout changes. This allowed us to reduce manual QA effort, improve regression coverage, and bring automation to legacy desktop systems where standard tools fall short.
Key Results:
Applied computer vision and OCR for robust UI element recognition
Built a custom framework for scriptless, image-based automation
Enabled test automation for legacy and non-standard desktop applications
Improved test stability across frequent UI updates and layout variations
Reduced manual QA load and improved regression reliability
Our expertise in adapting AI and computer vision for legacy QA challenges enables teams to achieve automation coverage even in environments where conventional tools break down.
We don’t just follow AI trends – we turn them into real business results. Here’s why our clients choose to work with us:
Our development process is designed to turn complex AI ideas into working, scalable solutions – with clear steps, fast validation, and measurable outcomes.
LLM Platforms: Jira, OpenAI, Anthropic, Mistral, Hugging Face
Dev Tools: Python, FastAPI, LangChain, n8n
MLOps & Infrastructure:Docker, MLflow, Airflow, Kubernetes
Computer Vision: Tesseract, SikuliX, OpenCV
Voice AI:Whisper, Speech-to-Text APIs
Prototyping: Replit, Cursor, low-code platforms
