Our goal is to help you launch and scale custom cloud-native AI solutions that drive revenue and eliminate operational complexity.
We turn your ideas and prototypes into production-ready AI solutions built to deliver measurable value to your business and partners.
What you get:
Our experts build high-performance data systems that process and structure your corporate knowledge to power real-time AI capabilities.
What you get:
We deliver custom applications powered by LLMs and GenAI that transform how your users interact with software and data.
What you get:
We can connect and optimize leading AI models, including OpenAI, Claude, Gemini, and Llama, for your unique operational requirements.
What you get:
Our team designs API-first AI services that allow your internal software, clients, or third-party applications to deal with AI features securely.
What you get:
Explore how we help organizations transform their core workflows and deploy scalable AI services tailored to their needs.
3 key platform pillars built
Skrivanek, an EU-based language services company, planned to launch a comprehensive language learning SaaS platform for the European market. Akveo engineered a scalable multi-tenant system from scratch. It features AI-powered content adaptation tailored to individual learner profiles, advanced role-based user management for corporate clients, and a streamlined payment system that supports flexible subscriptions and automated billing.
50% faster data retrieval
A global consulting firm needed to resolve critical data bottlenecks in its Factory Intelligence SaaS platform. To address this, Akveo engineered Factory Copilot, an AI assistant powered by Azure OpenAI and Semantic Kernel. It delivers real-time telemetry, production tracking, predictive maintenance alerts, and dynamic visual charts across SQL databases, PDFs, and SAP systems, all backed by strict role-based enterprise security.
1,500+ hours saved annually
A US-based AI startup wanted to modernize the web interface of its AI-powered platform for insurance brokers. Our team engineered a scalable React and Python web application that redesigned 10+ core workflows. The platform is now equipped with flexible chat interfaces, structured history, in-app document previewing, dynamic loading indicators, and Stripe payment integration.
Our goal is to help you launch and scale custom cloud-native AI solutions that drive revenue and eliminate operational complexity.
We build modular microservices and high-throughput API gateways designed to deliver low-latency AI responses across complex enterprise environments.
Our experts implement smart caching, dynamic model routing, and payload pre-processing to ensure that your cloud AI services stay cost-efficient as request volumes scale.
We create multi-tenant architectures with strict data isolation, role-based access control, end-to-end encryption, and full compliance frameworks to protect your proprietary data.
Our API-first approach guarantees that web apps, mobile solutions, internal platforms, or third-party partner systems can effortlessly interact with your custom AI capabilities.
Our engineering teams bring deep experience across industries and can align your AI platform with strict sector regulations and real-world business KPIs.
We continuously monitor end-to-end response speeds and server load to prevent slow performance and timeouts so that users can enjoy instant AI interactions.
We build resilient cloud AI services that can deal with high traffic without compromising performance or security.
We convert your industry-specific algorithms and data workflows into reliable cloud services designed for integration and low operational costs.
Our team engineers secure medical text extraction and record routing endpoints that run in isolated multi-tenant environments with strict role-based access control.
We build supply chain AI services to process multi-carrier shipping manifests, pull customs data, and update fleet management software in real time.
Our engineers implement custom document-intelligence services that parse underwriting files, extract policy risks, and process incoming claims automatically across secure environments.
We create industrial AI services that expose machine telemetry analysis and inventory query endpoints to connected factory systems.
Our developers can help you power your educational system with fast AI tools designed for personalized feedback and progress tracking.
We deliver scalable financial AI solutions that automate transaction risk scoring, loan verification, and document auditing while preserving complete data isolation between accounts.
We can package automotive domain logic into high-throughput cloud services to deliver real-time telemetry processing and supply chain updates with predictable infrastructure costs.
Our team delivers compliant AI systems designed to process environmental impact reports and automatically flag regulatory compliance risks across distributed energy projects.
We select reliable tools to ensure that your cloud AI services deliver low-latency performance and predictable infrastructure costs.
Find the right engagement model for your project.
We build a production-grade prototype to validate your technical concept. This allows you to evaluate response quality and business ROI before committing to a full-scale build.
Timeline & Pricing: 4-6 weeks, typically $15K
Our team engineers end-to-end software platforms customized to your exact operational needs and domain-specific compliance requirements.
Timeline & Pricing: 3-5 months, from $60K
We can add our senior AI and backend engineers to your team to solve complex infrastructure challenges and accelerate product releases.
Timeline & Pricing: Onboarding in 1-2 weeks, monthly rate
AI-as-a-Service gives companies cloud access to ready-made large language models and data processing tools through web APIs. To use such AI services, companies do not need to buy specialized hardware, set up GPU servers, or maintain internal data pipelines. They can rent these capabilities on demand. This delivery model lets teams embed computer vision or predictive algorithms into software without building and supporting the underlying AI infrastructure themselves.
By eliminating infrastructural complexity, this approach allows businesses to save money on expensive compute hardware and cut down on long-term server maintenance. Engineering teams can launch software faster as they need to connect to existing APIs instead of building model backends from scratch. Moreover, AIaaS systems can handle traffic spikes automatically without slowing down.
At Akveo, we build platforms with strict enterprise-grade security protocols, including RBAC, isolated multi-tenant architecture, and end-to-end encryption. Separate environments prevent information leaks between clients. Meanwhile, authorization rules limit who can touch specific resources. In addition, your prompt histories and customer datasets stay private and are never fed back into public model training datasets.
Yes, we have solid experience connecting modern cloud platforms to legacy tech stacks. With an API-first design approach, our team builds custom middleware and web services that link new algorithms to old SQL databases, internal CRMs, or ERP setups like SAP. This method lets you add fresh capabilities without replacing reliable core software or interrupting daily business operations.
We manage cloud spending through smart backend routing and data optimization. The application caches frequent requests, cleans raw payloads before sending them out, and routes simple tasks to smaller, low-cost models. High-capacity LLMs run only when complex logic demands them. This prevents surprise API charges and keeps hosting expenses predictable as user traffic increases over time.
95% of our partners continue working with us beyond the initial scope and more than 70% stay with us for 2+ years.
