Solutions
Projects scoped to outcomes, not hours.
Six ways companies put Quefly to work. Each starts with a written architecture sketch and delivery plan — before any contract — and ships in increments you can evaluate weekly.
Project
Fixed scope, delivered
A defined outcome with milestones and a handover — priced and planned in writing before we start.
Pod
An ongoing senior team
A dedicated, AI-accelerated team that builds and operates with you month over month — scale it up or down as the roadmap moves.
Advisory
Audits & architecture
Short, sharp reviews — platform, security, or cloud spend — that end in a written report your team can act on without us.
Internal Developer Platform
The situation
Shipping a service takes six teams, four tickets, and three weeks. Your best engineers spend their time on YAML instead of the product.
What we do
We build the paved road: a self-service platform where a new service — repo, pipeline, environments, observability, security baseline — is one commit. Golden paths encode your standards so compliance is the default, not a review comment.
What you get
- Service scaffold → production in under an hour
- Self-service environments: ephemeral previews, one-click databases and queues
- One platform team supports dozens of product teams
- Standards enforced by templates, not by nagging
- DORA metrics visible per team — lead time, deploy frequency, failure rate
Multi-Cloud Architecture & Migration
The situation
You’re on one cloud by history, moving to another by mandate, or on three by acquisition — and the bill and the blast radius are both growing.
What we do
Deliberate architecture across AWS, GCP, Azure, and OCI: landing zones, network topology, identity federation, and a migration executed in waves with rollback points — not a big-bang weekend. Portability where it pays, commitment where it doesn’t.
What you get
- Landing zones with security and cost guardrails from day one
- Cross-cloud identity: AWS IAM, Azure Entra ID, and Google Cloud IAM behind one SSO
- Migrations with zero-downtime cutovers and tested rollback
- FinOps in place: tagging, rightsizing, reserved capacity, showback per team
- A cloud bill someone can actually explain
Zero-Trust Security Program
The situation
A flat network, shared credentials, and a VPN from 2016 — one phished laptop away from a very bad quarter. The auditor’s spreadsheet isn’t helping.
What we do
Identity-first access done properly: SSO and MFA everywhere, short-lived credentials, segmented networks, continuous monitoring, and hardening driven by a real threat model — with compliance evidence generated by the platform itself.
What you get
- No standing credentials; access is scoped, logged, and expiring
- SIEM live and tuned — Google Chronicle, Microsoft Sentinel, or Splunk
- 24/7 visibility: monitoring, alerting, and audit trails across the stack
- Incident response ready: playbooks, tabletop exercises, escalation paths
- SOC 2 / ISO 27001 / PCI-DSS / DPDP evidence on tap
Cloud-Native Modernization
The situation
The monolith works — that’s the problem. Every deploy is a ceremony, every scale-up a purchase order, and the team that understood it has moved on.
What we do
Incremental modernization, not a rewrite: containerize, carve seams along real domain boundaries, move state carefully, and put delivery on rails. The system keeps serving traffic the whole time; the old path stays warm until the new one has earned trust.
What you get
- Deploys go from quarterly ceremony to daily non-event
- A containerized estate on Kubernetes with CI/CD rails and observability
- Data moved safely: replication-first migrations, no big-bang weekends
- Scale on demand instead of on procurement
- A system the current team can reason about
AI Enablement
The situation
Everyone bought AI tools; nobody changed the way work gets done. Usage is high, but delivery hasn’t sped up and nobody trusts the output enough to ship it.
What we do
We make AI part of how your team actually builds software: development workflows with review gates and guardrails your security team will sign off on, plus AI features in your own products — done safely, measured honestly.
What you get
- AI woven into your delivery workflow, with humans in control
- Model strategy across Claude, OpenAI, and Gemini — evaluated on your use case
- AI features in your product: search, assistants, document intelligence, automation
- Governance in writing: usage policy, data boundaries, monitoring
- Results measured in cycle time and quality, not hype
Enterprise Product Builds
The situation
You need a real product — not a prototype that demos well and dies in production. And you need it without spending a year hiring a team first.
What we do
A Quefly pod — senior engineers working with AI — takes the build end to end: architecture, implementation, security, launch, and operation. Weekly shippable increments, written decision records, and a codebase your future team will thank you for.
What you get
- From signed SOW to production in weeks, not quarters
- QA built in: automated tests, performance runs, UAT before every release
- UX/UI and accessibility (WCAG) as part of the build, not an add-on
- Handover-ready: docs, ADRs, runbooks, and clean CI from day one
- Option to operate long-term under an SLO, on-call included
Not sure which fits?
Describe the problem. We'll map the project.
A 45-minute call with an engineer, then a written proposal: architecture sketch, milestones, team shape, and cost. No discovery-phase invoice.