# Orzed

> Orzed is a senior-led AI, software and digital operations partner. We pair human product, engineering and review leads with the Orzed Console, our delivery platform, and a three-tier model stack (Orzed Horizon for planning, Orzed Meridian for execution, Orzed Pulse for high-frequency gates). Customers see the engagement run end to end: brief intake, planning, execution, evidence-backed QA, release.

Orzed, LLC, 8 The Green #10689, Dover, DE 19901. info@orzed.com.

## Start here

- [Orzed homepage](https://www.orzed.com/): What we do, the Console, model stack and engagement model.
- [About](https://www.orzed.com/about): How the team is structured, principles and accountability model.
- [Plans](https://www.orzed.com/plans): Three engagement models (Core, Prime, Enterprise Operations).
- [Solutions](https://www.orzed.com/solutions): Solution areas Orzed assembles around a product.
- [Technologies](https://www.orzed.com/technologies): Stack picks Orzed builds and operates in production.
- [Showcase](https://www.orzed.com/showcase): Production projects and case walkthroughs.
- [Careers](https://www.orzed.com/careers): Open roles and the working contract.
- [Contact](https://www.orzed.com/contact): Direct channels for enterprise access and intake.

## Plans

- [Core Plans](https://www.orzed.com/plans/core): Lighter engagements that need senior delivery without enterprise scope.
- [Prime Plans](https://www.orzed.com/plans/prime): Higher-velocity production for active product builds.
- [Enterprise Operations](https://www.orzed.com/plans/enterprise): Multi-stream operating layer for $5M+ revenue or high-consequence systems.

## Services

- [AI Model & API Integrations](https://www.orzed.com/services/ai-integration): assistants, copilots, retrieval, automation triggers, secure data connections.
- [Code & Performance Refactoring](https://www.orzed.com/services/code-performance-refactoring): legacy review, refactoring, perf repair, query optimization.
- [CRM & Revenue Operations](https://www.orzed.com/services/crm-revenue-operations): pipelines, lifecycle automation, segmentation, revenue reporting.
- [E-Commerce & Marketplace Build](https://www.orzed.com/services/ecommerce-marketplace): storefronts, vendor panels, catalogs, checkout, payments.
- [Growth Analytics & SEO/GEO](https://www.orzed.com/services/growth-analytics-seo): tracking architecture, ad analytics, search visibility, AI-search readiness.
- [Mobile Applications](https://www.orzed.com/services/mobile-app-development): iOS, Android, cross-platform, portals, field apps, release ops.
- [SaaS Product Development](https://www.orzed.com/services/saas-product-development): subscription products, portals, billing, RBAC, analytics.
- [Web & Content Platforms](https://www.orzed.com/services/web-content-platforms): corporate sites, headless CMS, multilingual, technical SEO, CWV.

## Technology

- [Artificial Intelligence](https://www.orzed.com/tech/artificial-intelligence): umbrella discipline map (ML, DL, CV, NLP, MLOps, data engineering).
- [Machine Learning](https://www.orzed.com/tech/machine-learning): classical ML, ranking, classification, propensity, fraud signals.
- [Data Engineering](https://www.orzed.com/tech/data-engineering): warehouses, lakes, streaming pipelines, contracts, governance.
- [Computer Vision](https://www.orzed.com/tech/computer-vision): detection, segmentation, OCR, visual search, video analytics.
- [Natural Language Processing](https://www.orzed.com/tech/natural-language-processing): extraction, classification, retrieval, generation, eval.
- [Deep Learning](https://www.orzed.com/tech/deep-learning): CNN, Transformer, diffusion, RLHF, distributed training, quantised inference.
- [MLOps](https://www.orzed.com/tech/mlops): feature stores, model registries, serving, monitoring, drift, retraining triggers.
- [Cyber Security & Risk Ops](https://www.orzed.com/tech/cyber-security): audits, access policies, vulnerability review, monitoring, compliance.

## Industries

- [Financial Technology](https://www.orzed.com/industries/financial-technology): banking, payments, capital markets, compliance-first delivery.
- [Healthcare & MedTech](https://www.orzed.com/industries/healthcare-medtech): regulated build, compliance panel, risk ledger.
- [E-Commerce & Retail](https://www.orzed.com/industries/ecommerce-retail): storefront, marketplace, operating metrics.
- [Manufacturing & Industrial](https://www.orzed.com/industries/manufacturing-industrial): OEE, throughput, plant systems, automation.
- [Media & Publishing](https://www.orzed.com/industries/media-publishing): reader rails, distribution, content automation.
- [Education & EdTech](https://www.orzed.com/industries/education-edtech): audience ladder, learning systems, content platforms.
- [Real Estate & PropTech](https://www.orzed.com/industries/real-estate-proptech): 6-stage deal flow, listings, transaction systems.
- [Logistics & Supply Chain](https://www.orzed.com/industries/logistics-supply-chain): 5-lane SLO contracts, control tower, integration.
- [Energy & Sustainability](https://www.orzed.com/industries/energy-sustainability): forecasting, dispatch, disclosure, DERMS.

## Management & operations

- [Project Management](https://www.orzed.com/management/project-management): scoping, ownership, delivery audits.
- [Product Strategy](https://www.orzed.com/management/product-strategy): executive planning, roadmaps, scope control, AI-era operating models.
- [Portfolio Management](https://www.orzed.com/management/portfolio-management): intake, gate, kill, scale rubric for multi-bet portfolios.
- [DevOps & Cloud Infrastructure](https://www.orzed.com/management/devops-cloud-infrastructure): cloud architecture, CI/CD, deployment, monitoring, scaling.
- [Enterprise Workflow Automation](https://www.orzed.com/management/enterprise-workflow-automation): routing, approvals, audit trails, agent-assisted ops.
- [Business Intelligence](https://www.orzed.com/management/business-intelligence): KPI dashboards, executive reporting, attribution, decision-ready data.
- [QA & Release Governance](https://www.orzed.com/management/qa-release-governance): automated tests, regression, QA agents, staging checks, release gates.
- [UX/UI Systems & Design](https://www.orzed.com/management/ux-ui-systems): design systems, conversion flows, dashboards, component libraries.
- [Change Management & Transformation](https://www.orzed.com/management/change-management): AKDAR-style adoption ladder, governance, rollout.

## Insights

Field-tested writing from the senior team. Categories below; see [/insights](https://www.orzed.com/insights) for the full feed.

- [Agent Systems](https://www.orzed.com/insights/category/agent-systems): Autonomous agents in production. Tool use, planning loops, multi-agent handoffs, memory design and the reliability patterns that decide whether an agentic system is a demo or a product.
- [AI Engineering](https://www.orzed.com/insights/category/ai-engineering): Field reports on shipping AI systems that survive production. Governance, evaluation, retrieval, prompt engineering and the operational scaffolding that keeps models accountable after launch.
- [Console Changelog](https://www.orzed.com/insights/category/console-changelog): Engineering notes from inside the Orzed Console. New automation in delivery, model and agent launches, routing changes, billing primitives, observability hooks. What we shipped, why it shipped, what it means for an engagement.
- [Data Platform](https://www.orzed.com/insights/category/data-platform): Data engineering, warehousing, retrieval infrastructure and observability. From schema design to vector store sizing, the patterns that keep an analytical and AI-ready data layer honest.
- [LLM Cost Engineering](https://www.orzed.com/insights/category/llm-cost-engineering): Token economics, model routing, prompt caching and context window management. The engineering work that decides whether an AI feature is a margin contributor or a margin killer.
- [MLOps](https://www.orzed.com/insights/category/mlops): Production machine learning beyond LLMs. Feature stores, model registries, training pipelines, monitoring and the operational discipline that keeps classical models honest in production.
- [Orzed How It Works](https://www.orzed.com/insights/category/orzed-how-it-works): Walkthroughs of the Orzed delivery model. How an engagement moves from brief to release, where senior review sits, how the Console organises the work and what the customer touches at each step.
- [Orzed Models & Agents](https://www.orzed.com/insights/category/orzed-models-and-agents): Model cards and agent write-ups for the Orzed stack. Horizon, Meridian and Pulse plus the agents built on top: Intake, Planning, QA, the Routing Layer. How they are trained, where they sit, what they do not do.
- [Product Operations](https://www.orzed.com/insights/category/product-operations): Running a product after launch. SLO design, on-call practice, incident response, customer signal triage and the operational rituals that keep a live product trustworthy at scale.
- [Security and Trust](https://www.orzed.com/insights/category/security-and-trust): Application and AI system security, access control, audit trails, regulatory mapping and the engineering practice that makes a system worth a regulator's signature and a customer's data.
- [Software Delivery](https://www.orzed.com/insights/category/software-delivery): How teams move code from a feature ticket to a customer-visible release without breaking the contract. Branching, review, release gates, rollback design and the small decisions that decide delivery speed.
- [Workflow Automation](https://www.orzed.com/insights/category/workflow-automation): Business process automation, ETL, internal tooling and the engineering judgement that decides between Temporal, n8n, Zapier or custom code. With and without LLMs in the loop.

## Insight articles

- [Move faster with senior product and engineering guidance](https://www.orzed.com/insights/move-faster-with-senior-product-and-engineering-guidance): How Orzed pairs senior product and engineering leads with AI accelerated execution. Where the senior call sits, where AI runs, how the Console surfaces both.
- [Orzed QA Agent, evidence based validation](https://www.orzed.com/insights/orzed-qa-agent-evidence-based-validation): Technical write up of the Orzed QA Agent. Pulse based composite with deterministic test runner plus security and static analysis. Evidence backed verdicts.
- [Why AI Integration Fails at the Governance Layer](https://www.orzed.com/insights/why-ai-integration-fails-at-governance): The model is rarely the failure. A missing prompt registry, evaluation gate and human approval path are where production AI integrations actually fall over.
- [Multi-Agent Handoff Patterns That Actually Work](https://www.orzed.com/insights/multi-agent-handoff-patterns-that-actually-work): Three handoff patterns for production multi-agent systems with the failure modes and observability hooks that decide whether the agents earn their keep.
- [Automated QA Agents are now live](https://www.orzed.com/insights/automated-qa-agents-are-now-live): The first automated layer of the Orzed Review pipeline is live. Built on Orzed Pulse with public security and static analysis models, evidence backed verdicts.
- [Agent Memory Design Beyond the Chat History](https://www.orzed.com/insights/agent-memory-design-beyond-the-chat-history): Three memory shapes for production agents: working memory, episodic memory, semantic memory. Picking the right one for the failure you are trying to fix.
- [LLM Cost Routing: The Cheapest Passing Model Pattern](https://www.orzed.com/insights/llm-cost-routing-cheapest-passing-model): Routing each request to the cheapest model that passes its eval cuts inference spend 30 to 50 percent. Architecture, routing logic and eval discipline.
- [Introducing Orzed Horizon, the flagship planning model](https://www.orzed.com/insights/introducing-orzed-horizon): Orzed Horizon is the flagship model in the Orzed stack. Long context, deep reasoning, sized for planning, architecture and senior review work. Async by design.
- [Introducing Orzed Meridian, the workhorse production model](https://www.orzed.com/insights/introducing-orzed-meridian): Orzed Meridian is the middle tier of the Orzed stack. Sized for everyday coding, content and structured output, with strong tool use and function calling.
- [Introducing Orzed Pulse, the always on lightweight model](https://www.orzed.com/insights/introducing-orzed-pulse): Orzed Pulse is the lightweight tier of the Orzed stack. Distilled from Horizon, sized for QA gates, classification, routing and sub second validation.
- [The Orzed Routing Layer, how models hand off work](https://www.orzed.com/insights/the-orzed-routing-layer): The part of the Orzed stack that decides which model handles each task. Cost, quality and latency optimisation across Horizon, Meridian and Pulse tiers.
- [Orzed Planning Agent, from brief to pipeline](https://www.orzed.com/insights/orzed-planning-agent-from-brief-to-pipeline): Planning Agent runs on Horizon and turns an approved brief into a Recommendation: blocks, dependencies, role assignment, throughput and cost estimates.
- [Orzed Intake Agent, brief comprehension at the front door](https://www.orzed.com/insights/orzed-intake-agent-brief-comprehension): The Intake Agent reads every customer brief that enters the Orzed Console. Built on Pulse, produces a structured Intake Report for the Technical Review Team.
- [Prompt Injection Defence Beyond Input Filtering](https://www.orzed.com/insights/prompt-injection-defence-beyond-input-filtering): Input filtering alone is not a defence against prompt injection. The layered architecture that keeps an LLM-driven system from being walked off its rails.
- [When to Use an Agent and When to Use a Pipeline](https://www.orzed.com/insights/when-to-use-an-agent-and-when-to-use-a-pipeline): Agentic loops cost more, fail strangely and resist debugging. The honest test for whether your problem needs an agent or just a deterministic pipeline.
- [Context Window Economics: The Hidden Bill on RAG](https://www.orzed.com/insights/context-window-economics-the-hidden-bill-on-rag): Stuffing context costs money on every call, even on tokens the model ignored. The discipline that keeps RAG context relevant, ranked and compressed.
- [Evaluating LLMs Without a Research Team](https://www.orzed.com/insights/evaluating-llms-without-a-research-team): A working evaluation gate that a small engineering team can build in a week, with the assertions, scoring and failure modes that make it production-credible.
- [EU AI Act Mapping for Engineering Teams](https://www.orzed.com/insights/eu-ai-act-mapping-for-engineering-teams): What the EU AI Act actually requires of an engineering team: the four risk tiers, the documentation burden, and the timeline that already started in 2025.
- [Prompt Registry: YAML File, Database Table, or Service?](https://www.orzed.com/insights/prompt-registry-yaml-table-or-service): Three working shapes for a production prompt registry, with the trade-offs that decide which one fits a team of three, thirty, or three hundred.
- [System Prompts That Survive Three Model Upgrades](https://www.orzed.com/insights/system-prompts-that-survive-three-model-upgrades): A system prompt tuned to one model's quirks breaks on the next model. The structural patterns that decouple intent from model-specific tuning.
- [Prompt Caching: Where It Pays Back and Where It Does Not](https://www.orzed.com/insights/prompt-caching-where-it-pays-back-and-where-it-does-not): Provider-side prompt caching cuts cached input cost by up to 90 percent. The pattern that earns the discount and the configurations that waste it.
- [LLM Output Streaming: The Edge Cases That Bite](https://www.orzed.com/insights/llm-output-streaming-the-edge-cases-that-bite): Token streaming is the default for chat UIs and the source of subtle bugs. Partial JSON, truncated outputs, retries and the patterns that handle them.
- [When RAG Actually Helps and When It Hides Bad Retrieval](https://www.orzed.com/insights/when-rag-actually-helps-and-when-it-hides-bad-retrieval): Retrieval-augmented generation looks like an answer to every grounding problem. The honest test for whether you need RAG, fine-tuning or a cleaner data source.
- [Vector Store Sizing: The Cost Truth Nobody Tells You](https://www.orzed.com/insights/vector-store-sizing-the-cost-truth-nobody-tells-you): What a million vectors actually costs across Pinecone, Qdrant, Weaviate and pgvector, and the configuration choices that move the bill by 5x.
- [Customer Signal Triage: From Noise to Roadmap](https://www.orzed.com/insights/customer-signal-triage-from-noise-to-roadmap): Support tickets, NPS comments, sales notes and analytics all carry signal. The triage system that turns the volume into prioritisable input.
- [Incident Postmortems That Produce Actual Learning](https://www.orzed.com/insights/incident-postmortems-that-produce-actual-learning): Most postmortems end as filed documents. The few that produce real change share a structure: blameless framing, contributing factors, and tracked follow-ups.
- [SLO Design for Products That Do Not Page Engineers](https://www.orzed.com/insights/slo-design-for-products-that-do-not-page-engineers): An SLO either protects sleep or burns it. The difference is in how the objective is defined, the window length, and the budget burn-rate alerts that fire.
- [On-Call Rotations That Do Not Burn Engineers](https://www.orzed.com/insights/on-call-rotations-that-do-not-burn-engineers): An on-call rotation that pages every shift loses engineers. Six structural choices that produce rotations engineers will stay on for years.
- [CI Pipeline Speed: The Three-Minute Rule](https://www.orzed.com/insights/ci-pipeline-speed-the-three-minute-rule): A CI pipeline over three minutes pushes the team out of flow. The four levers that consistently bring slow pipelines back inside the budget.
- [Code Review at Scale Without Becoming a Bottleneck](https://www.orzed.com/insights/code-review-at-scale-without-becoming-a-bottleneck): Code review either distributes context or stalls every PR. Three structural changes that keep review fast, useful and not unfairly loaded on seniors.
- [Branching Strategy for Teams That Actually Ship](https://www.orzed.com/insights/branching-strategy-for-teams-that-actually-ship): Trunk-based, GitHub flow, GitFlow, release branches: which one fits which team size, with the lead-time numbers that decide it instead of opinion.
- [Rollback Budget: The Overlooked Deployment Metric](https://www.orzed.com/insights/rollback-budget-the-overlooked-deployment-metric): Most teams measure deploy frequency. Few measure rollback time. Without a rollback budget, every release is a one-way bet and recovery is improvisation.
- [SOC 2 for Engineering Teams: The Evidence Plan](https://www.orzed.com/insights/soc-2-for-engineering-teams-the-evidence-plan): SOC 2 is less about new controls and more about evidence the controls already exist. The engineering work that turns 'we already do this' into a passing audit.
- [Secret Rotation Without an Outage](https://www.orzed.com/insights/secret-rotation-without-an-outage): Rotating secrets sounds simple until production breaks because two services hold different keys. The dual-key pattern that rotates with zero downtime.
- [When the Automation Itself Becomes the Incident](https://www.orzed.com/insights/when-the-automation-itself-becomes-the-incident): Automations fail silently more often than loudly. The observability and recovery patterns that catch a broken workflow before a customer reports it.
- [Automating the Internal Workflow Without Creating a Second Job](https://www.orzed.com/insights/automating-the-internal-workflow-without-creating-a-second-job): Most internal automation moves the work from doing the task to maintaining the automation. Patterns that keep maintenance below the original task cost.
- [Temporal vs n8n vs Zapier: Honest Comparison](https://www.orzed.com/insights/temporal-vs-n8n-vs-zapier-honest-comparison): Three workflow tools for three different teams. Reliability, ergonomics, self-hosting, AI-in-the-loop. The decision matrix without tool-fashion bias.
- [Warehouse Cost Control: The Quarterly Ritual](https://www.orzed.com/insights/warehouse-cost-control-the-quarterly-ritual): Snowflake, BigQuery and Redshift bills grow quietly until the CFO asks why. The quarterly ritual that catches offenders before emergency cost-cuts.
- [Streaming Data Pipelines: The Back-Pressure Trap](https://www.orzed.com/insights/streaming-data-pipelines-the-back-pressure-trap): Streaming pipelines work until the consumer falls behind the producer. Patterns that handle back-pressure without dropping data or stalling the source.
- [Feature Store Architecture: The Three Shapes](https://www.orzed.com/insights/feature-store-architecture-the-three-shapes): A feature store is a library, not a database. The three shapes that work in production and the engineering trade-offs that decide which one fits your team.
- [Model Monitoring Beyond Accuracy Drift](https://www.orzed.com/insights/model-monitoring-beyond-accuracy-drift): Accuracy drift is the easy signal to monitor and the late one. The five signals that catch a degrading model before customers notice the regression.
- [Shipping Classical ML in an LLM World](https://www.orzed.com/insights/shipping-classical-ml-in-an-llm-world): LLMs did not retire classical ML. The categories where gradient boosting and logistic regression still beat LLMs on cost, latency and reliability.

## Optional

- [Privacy policy](https://www.orzed.com/privacy): Data handling, GDPR/CCPA, contact for requests.