AI-First Cloud Solutions Built on Google Cloud Platform
Google Cloud Development Services
Google Cloud Platform (GCP) is the world’s most innovative cloud — built on the same infrastructure that powers Google Search, YouTube, Gmail, and Google Maps, serving billions of users every second. With industry-leading AI/ML (Vertex AI, Gemini), the fastest data analytics engine (BigQuery), fully managed Kubernetes (GKE), and a global network with 187+ edge locations, GCP delivers unmatched speed, intelligence, and developer experience. Spotify, Snapchat, Twitter/X, PayPal, and HSBC run on Google Cloud. We build, migrate, and manage GCP solutions that scale from startup MVPs to enterprise platforms processing petabytes of data. Whether you need Cloud Run serverless apps, GKE microservices, BigQuery data warehouses, or AI-powered applications with Vertex AI — we architect and deliver Google Cloud solutions that are smart, fast, and cost-efficient.
Our Google Cloud Development Services Include
We build cloud-native applications and infrastructure on Google Cloud Platform. From Cloud Run and Cloud Functions to GKE Kubernetes clusters and Cloud SQL, we use the full GCP ecosystem to deliver fast, intelligent, cost-efficient solutions. Google Cloud leads in data analytics (BigQuery processes petabytes in seconds), AI/ML (Vertex AI, Gemini, TensorFlow), and Kubernetes (Google invented it). With 40+ regions and a premium-tier global network, your application runs on the same infrastructure as Google Search and YouTube. We handle architecture, development, deployment, monitoring, and cost optimization.
Learn MoreWhat We Build For You on Google Cloud
Google Cloud Platform powers some of the most data-intensive, AI-driven, and globally scaled applications on Earth. From serverless Cloud Run apps and GKE Kubernetes clusters to BigQuery data warehouses and Vertex AI models — GCP gives you Google-grade infrastructure. Here is what we build.
Cloud-Native Application Development
We build modern, cloud-native applications on Google Cloud from the ground up. Using Cloud Run, Cloud Functions, App Engine, GKE (Google Kubernetes Engine), and Compute Engine, your application scales automatically from zero to millions of requests — and back to zero when traffic drops. We develop REST APIs with Cloud Run + Cloud Endpoints, GraphQL APIs with Apigee, real-time systems with Pub/Sub and Firestore listeners, and event-driven microservices using Cloud Tasks, Pub/Sub, and Eventarc. Your app runs on Google’s premium-tier global network — the same network that serves Google Search in under 200ms worldwide. We architect for high availability across multiple zones/regions with 99.99% SLA, automatic failover, and zero-downtime deployments.
GCP DevOps & CI/CD Automation
We set up end-to-end CI/CD pipelines on Google Cloud that automate your entire software delivery lifecycle. Using Cloud Build, Artifact Registry, Cloud Deploy, and Source Repositories (or GitHub/GitLab integration), we automate builds, tests, security scanning, container image creation, and rolling deployments to GKE or Cloud Run. We implement Infrastructure as Code using Terraform or Google Deployment Manager so your entire GCP environment is version-controlled and reproducible. We configure monitoring with Cloud Monitoring, distributed tracing with Cloud Trace, error tracking with Error Reporting, and centralized logging with Cloud Logging. We also set up Binary Authorization so only verified, signed container images deploy to production. Your team ships faster and safer.
Cloud Migration & Modernization
We migrate your on-premises applications, databases, and infrastructure to Google Cloud with minimal downtime. Whether you are moving from physical servers, VMware, AWS, Azure, or legacy hosting, we plan and execute the full migration: application assessment with Migrate for Compute Engine, database migration with Database Migration Service (DMS), lift-and-shift to Compute Engine VMs, or full re-architecture to Cloud Run / GKE. We modernize legacy apps to run on serverless Cloud Run, move databases to Cloud SQL (PostgreSQL, MySQL, SQL Server), AlloyDB, or Firestore, and containerize monoliths into microservices on GKE Autopilot. We use Google’s Transfer Appliance for large data moves and set up Cloud Interconnect for hybrid connectivity. Most migrations complete in 6–16 weeks.
BigQuery & Data Analytics Platform
We build enterprise data platforms on Google Cloud centered around BigQuery — the most powerful serverless data warehouse on the planet. BigQuery scans petabytes in seconds, charges per query (or flat-rate), and requires zero infrastructure management. We design ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark/Hadoop), Cloud Data Fusion, and Cloud Composer (Airflow) that ingest data from dozens of sources into BigQuery or a unified data lakehouse on Cloud Storage. We build Looker and Looker Studio dashboards, real-time streaming analytics with Pub/Sub + Dataflow, and ML models directly in BigQuery with BigQuery ML or Vertex AI. Your leadership gets live dashboards, automated reports, and predictive insights — all governed with column-level security and IAM policies.
Serverless & Microservices Architecture
We architect and build serverless systems on Google Cloud that scale infinitely and cost nothing when idle. Cloud Run serves containerized apps with automatic scale-to-zero and per-second billing — no cluster management needed. Cloud Functions handle event-driven workloads (HTTP triggers, Pub/Sub messages, Cloud Storage events, Firestore changes) with automatic scaling. For complex systems, we design microservices on GKE Autopilot with Pub/Sub for async messaging, Eventarc for event routing, Cloud Tasks for task queues, and Workflows for multi-step orchestration. Each service deploys, scales, and fails independently. We implement distributed tracing (Cloud Trace), structured logging (Cloud Logging), and service mesh (Anthos Service Mesh/Istio). You pay only for what you use.
Vertex AI & Machine Learning Solutions
Google Cloud leads in AI/ML, and we build intelligent applications using the full Vertex AI platform. We train, fine-tune, and deploy custom ML models using Vertex AI AutoML (no-code), Vertex AI Workbench (Jupyter notebooks), and Vertex AI Pipelines (MLOps). We integrate Gemini (Google’s most capable foundation model) into your apps via Vertex AI APIs for text generation, summarization, code generation, image understanding, and multi-modal reasoning. We also use pre-built AI services: Vision AI for image recognition, Natural Language AI for text analysis, Speech-to-Text/Text-to-Speech, Document AI for form parsing, and Translation API for 100+ languages. All models deploy on Vertex AI Endpoints with auto-scaling, A/B testing, and model monitoring for drift detection.
How We Work
Discovery
Workshops, research, and business goals alignment to define your vision and project scope.
Planning
Solution blueprint, technology stack selection, and roadmap for scalable digital growth.
Design
User-centred design, wireframes, prototypes, and interactive mockups for validation.
Development
Agile sprints, rapid prototyping, and continuous integration for faster, smarter delivery.
Testing
Quality assurance, performance testing, and security validation to ensure reliability.
Deployment
Go-live execution, training, and ongoing support to keep solutions future-ready.
Our clients and projects
Software solutions for monitoring Oil & Gas company
Our Front-End engineers work as part of the team of a US company — the leader in Digital Oilfield Solutions. The task was to create an upgraded version of a web-based solution that optimizes oil and gas equipment and answers critical questions about its condition and performance.
VIEW CASE STUDY ❯❯❯
“The quality of the work and engagement has been so good. They go beyond simply executing a task, story or test and are genuinely interested in understanding what the end user wants/needs.”
Media content management platform
ANC is a New York-based company that builds unforgettable digital experiences for brand marketing. Through immersive design and multimedia services, they transform commercial spaces — stadiums, entertainment venues, transit hubs, and trade centers.
VIEW CASE STUDY ❯❯❯
“They work to help develop our company instead of only being a third-party service provider. As a result, they’ve become a part of our company, which is very cool.”
ML-powered laboratory diagnostics software
Selux Diagnostics is a US biotech company transforming infectious disease diagnostics with rapid antibiotic susceptibility testing to combat antimicrobial resistance and enable personalized therapies.
VIEW CASE STUDY ❯❯❯
“INNERLUXES resources are embedded in our team and serve as an extension to our workforce. And during the inevitable crunch periods INNERLUXES was able to rapidly increase our access to a skilled resource pool.”
AI-powered automation platform
Our client provides an AI-based collaborative platform that helps SRE teams respond to production incidents using a breakthrough approach. With this product, they can adopt SRE methodologies and reduce toil while getting a unified view of incidents.
VIEW CASE STUDY ❯❯❯
“The reliability and quality of the work done by the team are impressive.”
Frequently Asked Questions
Got questions about Google Cloud development? Here are simple, honest answers to what people ask us most.
Why choose Google Cloud over AWS or Azure?
Choose Google Cloud if you need: the best data analytics (BigQuery is 10–100x faster than Redshift for large-scale queries), the best AI/ML platform (Vertex AI, Gemini, TensorFlow — Google invented modern AI), the best Kubernetes (Google created Kubernetes, GKE is the most advanced managed K8s), the fastest global network (Google’s private fiber network connects 187+ edge locations), and the simplest developer experience (Cloud Run lets you deploy a container with one command, scale to zero, pay per request). Google Cloud is also the most open cloud — no vendor lock-in, strong support for open-source tools (Kubernetes, TensorFlow, Apache Beam, Knative). Spotify, Snapchat, Twitter/X, PayPal, and Target run on GCP.
How much does Google Cloud development cost?
Google Cloud development has two costs: development/consulting and GCP infrastructure. Development: A simple cloud API or web app deployment costs $10,000–$30,000. A mid-sized project (microservices, CI/CD, data pipeline) runs $30,000–$100,000. A complex enterprise platform or migration costs $100,000–$500,000+. GCP infrastructure: A startup app with Cloud Run + Cloud SQL costs $10–$100/month (Cloud Run scales to zero). A mid-sized system with GKE + Cloud SQL + Pub/Sub runs $500–$5,000/month. Enterprise systems with BigQuery, multi-region GKE, and Vertex AI run $5,000–$50,000+/month. GCP offers sustained-use discounts automatically (no commitment required), committed-use discounts (save 40–57%), and $300 free credits for new accounts.
Can you migrate our systems to Google Cloud?
Yes — cloud migration is one of our core services. We handle every type of migration: lift-and-shift (VMs to Compute Engine using Migrate for Compute Engine), re-platform (databases to Cloud SQL, AlloyDB, or Spanner; apps to Cloud Run or App Engine), and re-architect (monolith to microservices on GKE). We use Database Migration Service for zero-downtime moves from MySQL, PostgreSQL, SQL Server, or Oracle to Cloud SQL/AlloyDB. For large data transfers, we use Transfer Appliance or Storage Transfer Service. We set up Cloud Interconnect or Cloud VPN for hybrid connectivity, migrate DNS to Cloud DNS, and configure Cloud CDN and Cloud Armor for global performance and security. Most migrations complete in 6–16 weeks with phased cutover and rollback plans.
What Google Cloud services do you work with most?
Our most-used GCP services: Compute — Cloud Run, Cloud Functions, GKE Autopilot, Compute Engine, App Engine. Databases — Cloud SQL, AlloyDB, Firestore, Cloud Spanner, Memorystore (Redis). Storage — Cloud Storage, Filestore. Networking — Cloud CDN, Cloud Load Balancing, Cloud DNS, VPC, Cloud Armor. DevOps — Cloud Build, Artifact Registry, Cloud Deploy, Terraform. Security — IAM, Secret Manager, Cloud KMS, Security Command Center, VPC Service Controls. Data — BigQuery, Dataflow, Dataproc, Data Fusion, Cloud Composer, Looker. AI/ML — Vertex AI, Gemini API, Vision AI, Natural Language AI, Document AI, Speech-to-Text. Messaging — Pub/Sub, Eventarc, Cloud Tasks, Workflows. We have deep hands-on expertise across the full GCP platform.
How long does it take to build a Google Cloud solution?
A simple GCP deployment (Cloud Run + Cloud SQL + Cloud Build CI/CD) takes 2–4 weeks. A mid-sized cloud-native application with GKE microservices, Pub/Sub, and Cloud Monitoring takes 6–14 weeks. A full enterprise migration with multiple apps, databases, and hybrid networking takes 3–8 months. Setting up a BigQuery data platform with Dataflow ETL and Looker dashboards takes 6–12 weeks. A Vertex AI custom model pipeline takes 4–10 weeks. We work in 2-week sprints, deploy to staging environments early, and your team can start testing within the first sprint. Infrastructure as Code (Terraform) means your entire GCP environment is reproducible and version-controlled.
Can you reduce our Google Cloud bill?
Almost certainly yes. Most companies overspend on GCP by 25–45% due to over-provisioned VMs, idle GKE clusters, unoptimized BigQuery queries, and missing committed-use discounts. We audit your GCP projects using Cloud Billing reports, Recommender API, and Active Assist: right-size Compute Engine instances, enable GKE Autopilot (Google manages node scaling), switch to Cloud Run for bursty workloads (pay per request, scale to zero), use Preemptible/Spot VMs for batch jobs (save 60–91%), apply committed-use discounts (save 40–57%), optimize BigQuery with partitioning/clustering and on-demand vs. flat-rate pricing, and move cold data to Nearline/Coldline/Archive storage (save 50–95%). We set up budget alerts and billing exports so you have full cost visibility. Typical savings: 25–45% without any performance impact.
Ready to Build on
Google Cloud Platform?
Tell us what you need. We will architect, build, and deploy your GCP solution — cloud-native apps, BigQuery analytics, Vertex AI models, GKE microservices, or full cloud migration. Free consultation, no strings attached.
Talk to Our GCP Experts