Services

End-to-end technology consulting.

From pipeline design to cloud architecture, we bring deep hands-on expertise to every engagement. Here's what we do — and how we do it.

01

DevOps Consulting

Transform how your team ships software.

We help engineering organizations move from slow, fragile release cycles to fast, reliable delivery. Our DevOps engagements cover culture, process, and tooling — in that order.

Typical engagement: 4–12 weeks, remote or on-site
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What you get

  • Reduced time-to-production from weeks to hours
  • Unified toolchain across dev, QA, and ops teams
  • Incident response playbooks and on-call structures
  • Developer experience improvements that stick

Our approach

We start with a current-state assessment — interviewing your engineers, mapping your delivery pipeline, and identifying the highest-leverage bottlenecks. From there we design a phased roadmap and work alongside your team to implement it.

02

CI/CD Pipelines

Ship code safely, frequently, and automatically.

We design and build automated build, test, and deploy pipelines that give your team confidence to ship multiple times a day — without manual gates or weekend deploys.

Typical engagement: 2–6 weeks, remote
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What you get

  • Fully automated build and test on every commit
  • Zero-downtime deployment strategies (blue/green, canary)
  • Pipeline-as-code with full version control
  • Rollback and recovery procedures built in from day one

Our approach

We audit your current pipeline, identify manual steps and flaky tests, then rebuild with GitHub Actions, GitLab CI, or your preferred platform. Every pipeline we build is documented, tested, and owned by your team.

03

Infrastructure as Code

Reproducible, version-controlled infrastructure at any scale.

We replace click-ops and snowflake servers with declarative infrastructure that can be reviewed, tested, and deployed like application code — using Terraform, Pulumi, or Ansible.

Typical engagement: 3–8 weeks, remote
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What you get

  • Full infrastructure defined in version-controlled code
  • Consistent environments across dev, staging, and production
  • Automated drift detection and remediation
  • Modular, reusable infrastructure components

Our approach

We inventory your existing infrastructure, identify what to codify first, and build a migration plan that minimizes disruption. We write the code, run the reviews, and train your team to maintain it.

04

Cloud Solutions

Architecture that scales with your business.

We design cloud-native architectures on AWS, Azure, and GCP that are secure, cost-efficient, and built for growth — not just for today's load.

Typical engagement: 4–16 weeks, remote or on-site
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What you get

  • Right-sized architecture with clear cost controls
  • Security and compliance baked into the design
  • Multi-region and high-availability configurations
  • Governance frameworks your team can operate independently

Our approach

We run a cloud readiness assessment, design the target architecture, and produce a detailed implementation plan. We can execute the build ourselves or work alongside your team as a technical partner.

05

Cloud Migration

Move to the cloud without the surprises.

We plan and execute cloud migrations — lift-and-shift, re-platforming, or full re-architecture — with a methodology that eliminates guesswork and keeps production stable throughout.

Typical engagement: 6–24 weeks depending on scope
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What you get

  • Detailed migration plan with risk assessment and rollback strategy
  • Zero unplanned downtime during cutover
  • Post-migration cost and performance benchmarks
  • Runbooks and documentation for ongoing operations

Our approach

We use a proven 5-phase approach: discover, assess, plan, migrate, optimize. Each phase has clear deliverables and go/no-go criteria so you always know where you stand.

06

MLOps

Production ML systems that actually work in production.

We bridge the gap between data science and engineering — building the infrastructure, pipelines, and monitoring that turn experimental models into reliable production systems.

Typical engagement: 6–16 weeks, remote or on-site
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What you get

  • Automated model training, evaluation, and deployment pipelines
  • Model performance monitoring and drift detection
  • Feature stores for consistent, reusable feature engineering
  • Reproducible experiments with full lineage tracking

Our approach

We assess your current ML workflow, identify where manual steps and inconsistencies live, and build the platform layer that makes your data science team faster and your models more reliable.

Not sure which service fits?

Tell us about your challenge and we'll help you figure out the right starting point.