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Frequently Asked Questions

Have questions about how we work, what we deliver, or whether we’re the right fit? Here are clear, straightforward answers to the most common things teams ask before partnering with Epsilon ASI—covering engagement models, timelines, security, and what success looks like.

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We embed alongside your engineers and operate like a high-leverage extension of your team—not a separate silo. We work in your repos, your tooling, and your environments, shipping production-ready changes with clear ownership and transferability.

  • We ship PRs in your repos (infra, pipelines, app changes)—no black boxes.
  • We align on a clear “definition of done” (operable, observable, rollbackable).
  • We keep ownership explicit: every change has an owner and acceptance criteria.
  • We leave reusable patterns (templates, runbooks, docs) so your team can continue independently.

No. We’re not a staffing vendor and we’re not trying to become your permanent engineering team. We accelerate high-impact initiatives and unblock your team with senior execution and production-grade patterns—then hand off so your team owns the result.

  • We augment your team to increase execution velocity.
  • We remove recurring pain: fragile platforms, unclear ownership, cost waste, slow delivery.
  • Our goal is autonomy: your team is stronger when we leave.

We’re strongest when the problem is technical, operational, and business-impactful—where engineering velocity, reliability, and cost intersect.

  • Sustainable cloud cost reduction (execution + guardrails, not just dashboards).
  • Kubernetes migrations & hardening (including zero-downtime cutovers).
  • Terraform / Infrastructure-as-Code operating models and platform standardization.
  • CI/CD modernization (GitHub Actions / GitLab CI) + GitOps workflows.
  • Observability, incident readiness, and reliability improvements (SLO-driven).
  • Production AI agents on Google Cloud (Gemini Enterprise / Vertex AI) with governance.
  • Legacy modernization without rewrites (incremental, low-risk modernization).

We measure success with outcomes that leadership cares about and engineers can directly influence. We baseline first, agree on targets, then verify results with data—so improvements are real, not subjective.

  • Cost: monthly spend reduction, unit economics (cost per request/event/customer), waste removed, guardrails preventing regression.
  • Delivery: deployment frequency, lead time for changes, pipeline duration, change failure rate.
  • Reliability: MTTR, incident frequency, SLO compliance, alert-noise reduction.
  • Platform: environment provisioning time, migration throughput, stability under load tests.

Week one is about clarity and momentum. We establish the baseline, build the execution plan, and ship meaningful improvements early—without creating future debt.

  • Day 1: Kickoff, access, constraints, success criteria, system walkthrough.
  • Day 2: Baseline measurement (cost, reliability, delivery), inventory of systems and spend drivers.
  • Day 3: Prioritized execution backlog (ROI, risk, owners, timelines).
  • Day 4: Ship 1–2 low-risk quick wins (e.g., pipeline speedups, easy cost savings, observability fixes).
  • Day 5: Deliver the plan + next milestones + measurable targets for the next 2–6 weeks.

We ship in controlled increments. We baseline first, roll changes out safely (often with canaries), and make rollback a first-class feature. Production is treated like production—every time.

  • Baseline first: measure current cost/performance/reliability before touching anything.
  • Incremental delivery: small scoped changes, not big-bang rewrites.
  • Risk scoring: low/medium/high risk changes with different rollout requirements.
  • Canaries + rollbacks: safe release patterns built into the plan.
  • Observability before cutover: dashboards/alerts exist before traffic moves.
  • Runbooks: “what happens if this breaks?” is answered in advance.

You get working systems and the artifacts to operate them—not just advice. Everything is built to be owned by your team after handoff.

  • Merged PRs in your repos (infra, pipelines, app code, configs).
  • Terraform modules and environment definitions (IaC you can reuse).
  • CI/CD pipelines and reusable templates (GitHub Actions / GitLab CI).
  • GitOps repo structure and deployment conventions (where applicable).
  • Dashboards, alerts, and monitoring rules (actionable, not vanity).
  • Runbooks and incident response playbooks.
  • Architecture notes and a prioritized backlog with owners + ROI estimates.

Knowledge transfer is built into delivery, not added at the end. We ship improvements in your repos with your engineers involved, then leave templates and documentation that make the “next one” easy.

  • We implement in your tooling with your team watching and contributing.
  • We standardize patterns (templates, modules, conventions) so engineers can replicate.
  • We document decisions where your team already lives (README, ADRs, runbooks).
  • We run enablement sessions and handoff checklists so ownership is real.

We optimize for time-to-first-value. Most teams see meaningful progress in the first 1–2 weeks, then measurable outcomes within a few sprints depending on scope and change control.

  • 1–2 weeks: baseline + prioritized plan + first quick wins shipped.
  • 2–6 weeks: measurable improvements (cost wins, pipeline speed, reliability fixes, migration groundwork).
  • 6–12 weeks: larger platform outcomes (migration waves, deeper FinOps execution, production agent rollout).

Most engagements fit into one of three models. We’ll recommend the smallest engagement that can produce meaningful outcomes.

  • Diagnostic (1–2 weeks): baseline + opportunity map + execution plan + a couple quick wins.
  • Execution Sprint (4–8 weeks): ship outcomes—savings, migrations, delivery modernization, reliability improvements.
  • Retainer/Partner Model (ongoing): continuous improvement + governance + reliability + iterative delivery.

We can do either. Fixed scope works best when requirements are stable and bounded. Time & materials works best when there are unknowns and we want to optimize for outcomes over rigid scope.

  • Fixed bid: best for well-bounded work with clear acceptance criteria.
  • Time & materials: best for complex systems with unknown constraints.
  • Common pattern: fixed-price diagnostic → scoped execution sprint.

We focus on modern cloud-native stacks. We’re strongest with Kubernetes, IaC, CI/CD, observability, and production delivery patterns across the major clouds.

  • Google Cloud: Cloud Run, GKE, Vertex AI, IAM, networking, monitoring.
  • AWS: EKS/ECS, RDS, IAM, VPC, cost optimization patterns.
  • Kubernetes everywhere: Helm, GitOps, autoscaling, reliability hardening.

Yes. We routinely operate in environments with governance, auditability, and change-control requirements. We adapt to your policies while keeping delivery moving.

  • Least-privilege IAM patterns and workload identity approaches.
  • Private networking constraints and secure connectivity patterns.
  • Audit logging and traceability for infrastructure and deployments.
  • Approval-based change control with safe rollout and rollback practices.

Yes—especially when the goal is production value, not demos. We build agents that are observable, secure, testable, and integrated into real workflows.

  • Use case selection and ROI modeling (support triage, ops automation, engineering enablement).
  • Tool calling and structured outputs (reliability-first integration design).
  • Sessions + memory patterns with governance (PII handling, retention policies, deletion).
  • Evaluation and monitoring so agents stay reliable and affordable over time.

To move quickly, we need a clear owner, access aligned to the scope, and a way to ship changes (PR reviews, CI access, and change windows). If access is constrained, we can start with a diagnostic and a plan.

  • A primary technical owner (and ideally an executive sponsor).
  • Repo access and cloud/billing visibility (read-only is fine to start).
  • A clear target outcome (reduce spend, modernize delivery, build agents, migrate platforms).
  • A path to production: PR review process, approvals, and deployment windows.

We stay lean and senior. You work directly with engineers who ship production changes—not layers of management. We optimize for speed, clarity, and measurable outcomes, without the overhead of large teams and heavy process.

  • Senior, hands-on engineers (not a team of coordinators).
  • Production outcomes over slide decks.
  • Fast time-to-first-value with incremental, low-risk execution.
  • Reusable templates and knowledge transfer so you’re not dependent on us.
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