Architecture
Architecture, not wrappers.
Production AI systems built from open-source models, structured delegation pipelines, YAML workflow specs, and auditable tool integrations.
Architecture
Architecture, not wrappers.
Open-source models are only the starting point. The advantage comes from routing, delegation, defined workflows, integrations, and auditable output — built as one system.
Open-Source Models
Best-fit model per task
DeepSeek, GLM, Qwen, Nemotron — select the optimal model for each operation without vendor lock-in.
Model Router
Task-aware orchestration
Intelligent routing directs queries to the most capable model based on complexity, latency, and cost requirements.
Structured Delegation
Specialist agents by role
Complex tasks decomposed into subtasks handled by specialized sub-agents with focused capabilities.
YAML Workflows
Inspectable pipeline specs
Every pipeline defined in plain YAML — review, version, and iterate on workflow logic without touching code.
Tool Integrations
APIs, databases, docs, CRMs
Native connectors to the tools your team already uses — no rip-and-replace required.
Auditable Output
Logs, reviews, ownership
Every decision and output is logged, traceable, and reviewable — built for compliance and continuous improvement.
Open-Source Models
Best-fit model per task
DeepSeek, GLM, Qwen, Nemotron — select the optimal model for each operation without vendor lock-in.
Model Router
Task-aware orchestration
Intelligent routing directs queries to the most capable model based on complexity, latency, and cost requirements.
Structured Delegation
Specialist agents by role
Complex tasks decomposed into subtasks handled by specialized sub-agents with focused capabilities.
YAML Workflows
Inspectable pipeline specs
Every pipeline defined in plain YAML — review, version, and iterate on workflow logic without touching code.
Tool Integrations
APIs, databases, docs, CRMs
Native connectors to the tools your team already uses — no rip-and-replace required.
Auditable Output
Logs, reviews, ownership
Every decision and output is logged, traceable, and reviewable — built for compliance and continuous improvement.
Open-Source Models
Best-fit model per task
DeepSeek, GLM, Qwen, Nemotron — select the optimal model for each operation without vendor lock-in.
Model Router
Task-aware orchestration
Intelligent routing directs queries to the most capable model based on complexity, latency, and cost requirements.
Structured Delegation
Specialist agents by role
Complex tasks decomposed into subtasks handled by specialized sub-agents with focused capabilities.
YAML Workflows
Inspectable pipeline specs
Every pipeline defined in plain YAML — review, version, and iterate on workflow logic without touching code.
Tool Integrations
APIs, databases, docs, CRMs
Native connectors to the tools your team already uses — no rip-and-replace required.
Auditable Output
Logs, reviews, ownership
Every decision and output is logged, traceable, and reviewable — built for compliance and continuous improvement.
Operations
How the system operates
Every workflow follows the same four-stage architecture — model selection, role delegation, workflow specification, and validated output.
Select the best-fit model
Each task is routed to the model that best matches its capability, cost, and reliability requirements. No single default API — the router chooses from open-source and commercial models per operation.
Delegate by role
Research, retrieval, coding, review, and validation are separated into specialist sub-agents. Each agent has focused instructions, tools, and guardrails — no single prompt tries to do everything.
Define workflows in YAML
Repeatable, inspectable, version-controlled workflow specs replace fragile prompt chains. YAML definitions encode pipeline steps, model routing rules, tool calls, and validation gates — readable by both humans and systems.
Validate and log outputs
Commands, tests, reviews, execution traces — every output is captured and auditable. Human handoff points are built in where risk matters. You see exactly what the system did and why.
Philosophy
Why open-source-first
Open-source models are not a cheap alternative — they are a strategic advantage. The architecture is built to leverage that advantage at every layer.
Better model choice
Access to DeepSeek, GLM, Qwen, Nemotron, Llama, Mistral, and dozens more. Each task uses the model best suited to it — not the one model a vendor wants to sell you. Improvement cycles measured in weeks, not quarters.
Lower operating cost
No per-token tax when models are self-hosted or routed efficiently. Open-weight models remove the margin between raw inference cost and what closed APIs charge. Budgets scale with usage, not API price hikes.
No vendor lock-in
Models can be swapped, fine-tuned, or replaced without re-architecting the system. The pipeline and workflow layers are model-agnostic. Switching costs are zero by design.
Private or hybrid deployment
Run entirely on your own infrastructure, use a hybrid cloud split, or let us manage the hosted stack. Sensitive workloads stay internal; burst capacity routes to cloud. You choose the boundary.
Full ownership and auditability
Every YAML spec, every routing decision, every model response is yours. No black boxes, no shared infrastructure, no data leaving your control without explicit approval. The system is designed to be inspected.
Continuous improvement
Open-weight ecosystems evolve faster than any single vendor. New state-of-the-art models appear monthly. The architecture is designed to test, benchmark, and adopt improvements without downtime or migration projects.
Deployment
Deployment without lock-in
The same architecture runs in multiple configurations. Choose the model that fits your risk profile, budget, and operational constraints — and change it later without starting over.
Hosted managed setup
Fully managed infrastructure — we handle model serving, pipeline orchestration, monitoring, and updates. You get a working system without managing GPUs or Kubernetes. Best for teams that want to focus on outcomes, not operations.
Client-owned cloud
Deployed to your AWS, GCP, or Azure account. The infrastructure is yours — we provide the architecture, configuration, and deployment tooling. You control access, compliance boundaries, and cost allocation.
Private / internal deployment
Entirely air-gapped or on-premise. Models run on your hardware or private cloud. No external API calls, no data leaving your network. Designed for regulated industries and environments where data residency is non-negotiable.
Hybrid routing
Sensitive or internal workloads use private models; burst or experimental tasks route to cloud-hosted models. The model router enforces the split automatically. You get the best of both without managing two separate systems.
Who you work with
Built by operators, deployed by specialists
Optimized Workflow is operator-led and built for practical deployment, not agency overhead.
System design
Adam Normandin leads system architecture and implementation — model routing, pipeline orchestration, deployment, and security. Every system is built for real workflows, not slideware.
Business translation
Andrew Normandin supports business development and customer relationships, bringing a B.S. in Mathematics and an M.S. in Data Analytics for Science from Carnegie Mellon University, along with experience developing advanced AI systems, machine learning models, and neural network architectures.
Specialist engineering
For specialized engineering requirements, we bring in experienced technical engineering partners when deeper domain expertise is required — without the overhead of a large agency.