Multi-Provider AI Custom Product Development on AWS by Horizon Digital

Horizon Digital builds full production-grade AI products on AWS using whichever LLM provider best fits the use case — Amazon Bedrock, OpenAI, Anthropic via direct API, Google Gemini, Cohere, Mistral, or open-source models hosted on Amazon SageMaker. The product runs on AWS regardless of which model provider sits behind it.

Why a multi-provider listing exists separately from our Bedrock-only listing:

• Some clients have an existing provider relationship (e.g. OpenAI Enterprise) and want to keep their billing there.
• Some use cases require a model or capability that Bedrock does not currently expose (e.g. fine-tuning of a specific OSS model, real-time multimodal endpoints, or a model with specific data-residency constraints).
• Some clients want a defensive architecture that can fail over between providers.

Across all of these, Horizon Digital delivers the same production-grade outcome: a hardened, evaluated, observable AI product.

What we deliver:

• Production AWS architecture: API layer, retrieval-augmented generation (RAG), vector store on Amazon OpenSearch or Aurora pgvector, guardrails, secrets management, observability.
• LLM provider abstraction so the product is not locked to one vendor: a clean adapter layer over the chosen primary provider, with an optional fallback to a secondary provider.
• Hardened data pipeline: ingestion, chunking, embedding, vector store, refresh cadence, lineage. Embedding model selection per data type.
• Evaluation harness in CI/CD: gold-standard test set, evaluators for groundedness, accuracy, safety, latency, and cost — applied across all in-scope providers so swaps are quantified, not guessed.
• Observability: Arize Phoenix or equivalent for trace, span, and feedback capture; alerting on drift, cost, and quality regressions.
• Operational handover: runbooks, on-call procedures, prompt versioning policy, model upgrade playbook, vendor change procedure, cost controls.

Typical AWS services in scope: Amazon SageMaker AI, Amazon Bedrock (when chosen), Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, Amazon OpenSearch Serverless, Amazon S3, AWS Lambda, Amazon API Gateway, Amazon CloudFront, AWS Step Functions, AWS Secrets Manager, Amazon Cognito or Microsoft Entra ID federation, Amazon CloudWatch and AWS X-Ray. External providers integrated under the abstraction layer: OpenAI API, Anthropic API, Google Vertex AI / Gemini, Cohere, Mistral, open-source models hosted on SageMaker.

Who this is for:

• SMB AI Product (8 weeks): single-use-case AI product with RAG over a defined corpus, single primary LLM provider chosen at engagement start, 1 to 2 integrations, single-region AWS deployment, baseline evaluation suite.
• Enterprise AI Product (16 weeks): multi-use-case AI platform with agentic workflows, multi-provider abstraction with fallback, larger corpus, deeper integrations, multi-environment deployment, rigorous evaluation harness, observability and cost-governance dashboards.

Why Horizon Digital:

• AWS AI Services Competency partner with live Bedrock production deliveries plus engineering experience integrating OpenAI, Anthropic, and OSS models.
• Australian-based delivery. Compliance aligned to the Australian Privacy Principles (APP).
• Vendor-neutral engineering. We do not push you toward a provider for relationship reasons — provider choice is driven by use-case fit, cost, performance, and your existing commercial footprint.