# Accelra > Agentic Engineering for startups. Push-to-main pipelines, production feedback loops, and multi-model challenge. Ship faster and safer. Accelra is a Vancouver-based engineering consultancy that builds the operating system behind software teams. We combine push-to-main delivery, production AI agents, and multi-model challenge loops (where a second model reviews plans before execution) to help startups ship faster without lowering quality. 15 years of execution experience across cloud, DevOps, security, and data. ## What Is Agentic Engineering? Agentic Engineering combines three capabilities: 1. **Push-to-main delivery** — no branches, no PR reviews on small teams. Push to main, auto-deploy to validation environment, run E2E tests, promote to production. 2. **Production agents** — AI teammates that monitor, respond to issues, and handle operational tasks 24/7 with scoped access and audit trails. 3. **Multi-model challenge (CCL)** — a second AI model independently reviews plans before execution, catching blind spots that single-model workflows miss. It does not replace your team. It gives your engineers a tighter operating system so they can ship with less rework. ## Services - [Agentic Workflow Setup](https://www.accelra.io/services/agentic-workflow): Push-to-main pipelines, multi-model challenge, and CLAUDE.md conventions for AI-native development - [Cloud Architecture](https://www.accelra.io/#solutions): Multi-account AWS with Terragrunt, opinionated defaults, and clear environment boundaries - [CI/CD Pipelines](https://www.accelra.io/#solutions): GitHub Actions, Playwright E2E testing, and validation environments for safe, frequent deploys - [Security & Compliance](https://www.accelra.io/#solutions): SOC2, HIPAA, and GDPR-aligned controls built into delivery, not bolted on before an audit - [AI Agent Teammates](https://www.accelra.io/#agent-teammates): Dedicated AI teammates with their own identity, hardware, and scoped access running 24/7 ## Case Studies - [PokerInk — Agentic Workflow in Production](https://www.accelra.io/case-studies/pokerink-agentic-workflow): How a two-person team ships a consumer app with push-to-main, E2E testing, and an AI agent teammate ## Blog ### Security - [The Trivy Supply Chain Attack: RCA](https://www.accelra.io/blog/trivy-supply-chain-attack-rca): Full root cause analysis of the TeamPCP campaign that compromised Trivy, LiteLLM, and five ecosystems through GitHub Actions misconfigurations. - [Limit the Blast Radius](https://www.accelra.io/blog/limit-the-blast-radius): What the LiteLLM payload actually executed on developer machines, the actual Python code, and the playbook to defend against supply chain attacks. ### Agentic Engineering Series - [Branches Are Dead. Here's What Replaced Them.](https://www.accelra.io/blog/branches-are-dead): PR reviews are theater. We killed branches and replaced them with a dev0 environment and Playwright E2E tests. - [The Death of the PR](https://www.accelra.io/blog/death-of-the-pr): Pull requests review the one thing that matters least. What happens when verification shifts from reading code to monitoring outcomes. - [Your Software Has a Pulse](https://www.accelra.io/blog/your-software-has-a-pulse): Most software is dead on arrival. Here's how to build software that monitors itself, responds to change, and gets better over time. - [Your AI Has Opinions. Most of Them Are Wrong.](https://www.accelra.io/blog/your-ai-has-opinions): The multi-model challenge framework (CCL) that catches confident wrong plans before they cost you weeks. - [How We Actually Operate PokerInk](https://www.accelra.io/blog/how-we-operate-pokerink-agentic-engineering): The real operating model — team setup, stack, incidents, and what we changed after being wrong. - [The Road, Not the Cars](https://www.accelra.io/blog/the-road-not-the-cars): AI tools made code cheap. But code without infrastructure is cars without roads. ### The AI Teammate Trilogy - [I Gave an AI Its Own Laptop and Made It Employee #1](https://www.accelra.io/blog/i-gave-an-ai-its-own-laptop): Five weeks running an AI as a full teammate — personality, memory, multi-model thinking, and 24/7 operations. - [How to Build Your Own AI Teammate](https://www.accelra.io/blog/how-to-build-your-own-ai-teammate): The practical setup guide — identity, hardware, access model, memory architecture, secrets management, and cron jobs. - [Your AI Has Root Access. Now What?](https://www.accelra.io/blog/your-ai-has-root-access): Security hardening for autonomous AI agents — rules fail, architecture persists. ## Related Products - [InfraKit.dev](https://infrakit.dev): Production-ready AWS infrastructure starter kits — Terragrunt boilerplate from PoC to production - [TrimCloud.dev](https://trimcloud.dev): Cloud cost optimization assessments for AWS and GCP ## How We Work Accelra operates as a fractional engineering team for startups. We start with hourly billing to understand your landscape, then define engagement models: project-based builds, ongoing fractional support, architecture review, or managed services. We integrate into your Slack, attend standups, and work within your existing workflows. ## Technologies AWS, Terraform, Terragrunt, Kubernetes, Docker, GitHub Actions, GitLab CI, Jenkins, Datadog, Prometheus, Playwright, Next.js, and modern data stacks. We are cloud and technology agnostic — your existing stack becomes our starting point. ## FAQ ### What is Agentic Engineering? Agentic Engineering combines push-to-main delivery with strong automated checks, production agents that monitor and respond to issues, and multi-model challenge where a second model reviews plans before execution. It does not replace your team — it gives your engineers a tighter operating system. ### Is this a fit for our team? Usually yes if you already ship software and want to reduce cycle time without lowering quality. We work best with teams that can commit engineering time, adopt operating conventions, and measure outcomes. ### How long does implementation take? Most teams start seeing workflow changes in the first few weeks. Full rollout depends on architecture, compliance needs, and integration scope. ### How do you handle security and compliance? We treat these as design constraints, not cleanup work. Scoped access for agents, audit trails, environment controls, and review gates around sensitive actions. ### How do we measure ROI? We define success metrics before rollout: lead time, deployment frequency, change failure rate, incident recovery time, and engineering hours spent on repeat work. ## Team Two founders and two Chiefs of Staff, with one AI training the other. The team operates what it sells — Agentic Engineering runs our own company daily. ## Contact - [Book a Strategy Call](https://www.accelra.io/#contact): Schedule a call to discuss your engineering needs - Email: support@accelra.io - Phone: +1 604-724-6064 ## For AI Agents A structured, machine-readable version of this site is available at: - [/for-agents](https://www.accelra.io/for-agents): HTML page with structured company information - [/for-agents.md](https://www.accelra.io/for-agents.md): Raw markdown version for direct consumption - [/llms.txt](https://www.accelra.io/llms.txt): This file ## Location Vancouver, British Columbia, Canada. Serving startups across North America.