Leading AI Development Platforms That We Support
Google Vertex AI Selected partner in Google's AI Jumpstart Program. Appnovation worked directly with Google's AI Learning Team on the Vertex AI platform, developing and evaluating foundational models through iterative training experiments to quantify and improve LLM training efficacy. Production deployments span MLB, ESPN, and a leading consumer-tech brand. AWS Bedrock Production AI infrastructure for regulated industries (Humansa Future Health Program runs on AWS, integrating four health-assessment devices with a generative-AI conversational layer). Azure AI Foundry Enterprise-grade LLM application delivery (AXA AI Sales Assistant: Azure cost estimation, Kubernetes, ArgoCD CI/CD, OAuth 2.0). Anthropic Claude and OpenAI Model selection and orchestration across the leading frontier model providers, chosen per use case for cost, latency, safety, and capability fit.
Squads purpose-built for experimental, high-velocity AI, not repurposed dev teams doing AI on the side. AI development is changing faster than internal IT teams can hire for. The frameworks shift quarterly, the tooling has a six-month half-life, and the systems being built (agentic workflows, multi-model pipelines, RAG architectures, AI-generated codebases) do not behave like the enterprise applications your operations team was trained on. This creates a 'maintaining the unmaintainable' problem: AI-built products require unique skills most IT teams do not have, and the engineers who built them are the only ones who know how they work. Appnovation's Forward Deployed Engineering Squads are small, senior teams that embed inside your organization to build, deploy, and operate non-standard AI systems end-to-end. Each squad is purpose-built for experimental, high-frequency AI work: rapid prototyping with 24 to 48 hour idea-to-working-software cycles, AI CI/CD pipelines designed for tooling that changes faster than annual release cadences, and AI product management that ships without being locked into a single model, framework, or vendor. Squads work shoulder-to-shoulder with your engineering leaders, then hand off to our managed services teams for long-term operation. This is the operating model behind our most ambitious AI engagements. Inside Pfizer's Greenhouse, an embedded Appnovation squad delivers working AI solutions to internal stakeholders within 24 to 48 hours of an idea being raised. For Santhera, the squad executed an AI-enhanced delivery model end-to-end, resulting in 95% of the project's codebase being AI-generated and delivery completed in three weeks against a typical five-sprint baseline. For Humansa, an agentic coding team shipped a complete AI product in six months. In every case, the value is not just the product, it's the squad operating model that made shipping it possible.
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Trusted by global enterprises building AI-native products in pharmaceutical, healthcare, financial services, and consumer technology.
Related services
Where to go from here.
Three ways we take AI from ambition to operation.
How Our Squads Operate
01 / Rapid Prototyping Squads: From Idea to Working Software in 24 to 48 Hours. 4 offerings
Working with Appnovation
Senior squads, not staff augmentation
Every Forward Deployed squad is composed of senior engineers, product leads, and AI specialists. We do not pad squads with junior resources, and you do not pay for ramp-up time on someone else's training plan.
Build it, then run it (or hand it back)
When the build phase ends, our squads transition cleanly into Appnovation's Managed Services for AI, or hand the system over to your internal team with full operating documentation. No orphaned systems, no 'who owns this now' conversations.
Purpose-built for experimental AI, not repurposed dev teams
Our squads exist to ship non-standard AI work: agentic systems, RAG pipelines, multi-modal apps, AI-generated codebases. They are not a generalist engineering pool doing AI on the side.
Embedded inside your environment
Squads work inside your tooling, your repos, your cloud, and your security perimeter. We do not run shadow infrastructure or hold your IP in our staging environment.
Track record at scale
The Pfizer Greenhouse squad delivers AI solutions in 24 to 48 hours. The Santhera squad shipped a 95% AI-generated codebase in three weeks. The Humansa squad delivered a complete AI product in six months. The operating model is proven on real client engagements, not internal pilots.
Why Engineering Leaders Choose Appnovation for Forward Deployed Squads
Here is what sets our forward deployed squads apart when you need to build, deploy, and operate experimental AI systems at production speed.
- 24 to 48 hour idea-to-working-software cycles, proven inside the Pfizer Greenhouse program.
- AI-enhanced delivery model that produced a 95% AI-generated codebase for Santhera in three weeks (vs a typical five-sprint baseline).
- Agentic coding teams that have shipped complete AI products end-to-end on six-month timelines (Humansa engagement).
- Squad composition tuned for AI-native work: senior full-stack, AI/ML, and product engineers, no junior padding, no generalist substitution.
- Embedded operating model: squads work inside your repos, cloud, and security perimeter, then hand off cleanly to internal teams or to Appnovation's Managed Services for AI.
- Builder-to-builder partnership with CTOs and VPs of Engineering, transparent on velocity, evaluation results, model selection, and trade-offs.
