Coralmatrix

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Engagements

AI, fullstack, and cloud work that survives contact with production.

We take the parts of the stack that stall: models, platforms, and migrations. You get something your team can run on Monday.

Applied AI

Analyze the problem. Build the feature.

We start by analyzing the use case, then we build smart AI features your team can run: RAG, agents, evals, and a path to production. We do not stop at a notebook accuracy number.

  • Use-case analysis and data contracts
  • Smart AI features: RAG, agents, and LLM applications
  • Training, fine-tuning, and evaluation harnesses
  • Inference, drift, and operator runbooks

Engineering

Fullstack development

Product interfaces, APIs, and the data path between them. One team from the screen to the database, with the same bar we use for platforms.

  • Web applications and operator consoles
  • APIs, auth, and service boundaries
  • Data models and the UI that uses them
  • Tests, CI, and a handoff your team can own

Cloud

Architecture you can defend

Landing zones, identity, networking, and the runtime for APIs and data. Built for the review that happens after the architecture slide.

  • Multi-account and landing-zone design
  • API and event platforms
  • Observability, secrets, and least-privilege identity
  • Cost, reliability, and capacity as first-class constraints

Integration

Systems that have to talk

APIs, events, and integration platforms so sales, ops, and data are not waiting on a spreadsheet or a nightly file drop.

  • API, event, and queue design between systems
  • MuleSoft and other iPaaS flows, with contracts you can test
  • Identity, mapping, and error handling at the boundary
  • Runbooks for the team that inherits the integrations

Modernization

Platforms that have to move

Gateway and integration programs, including Apigee to MuleSoft, sequenced with Migration Agent and a cutover you can rehearse.

  • Inventory of proxies, products, and policies
  • Target mapping and gap analysis
  • Pilot, dual-run, and backout
  • Handoff to the team that inherits the platform

Cost

Evaluate spend. Then a plan.

We review how the estate actually burns money, then come back with a comprehensive plan to optimize cost: what to cut, what to resize, and what to change in the architecture so the savings hold.

  • Spend and usage review across cloud and platforms
  • Rightsizing, idle cleanup, and pricing-model choices
  • Architecture changes that reduce the bill without starving the system
  • A sequenced plan with owners, savings, and a way to measure

Pairing

Services sit on top of real estates.

If the problem is an API platform move, we can apply Migration Agent for Apigee to MuleSoft and other APM-to-APM paths. That is work we have used with clients. Custom engineering fills the gaps.

Plan an engagement

Integration

APIs, events, and iPaaS flows that connect the systems you already run.

Gateway programs

Apigee, MuleSoft, and the messy middle of products, apps, and shared policies.

Fullstack products

The interface, the API, and the data model, shipped as one system.

ML platforms

Feature paths, model registries, and inference that finance and security will sign.

Cloud foundations

The boring, load-bearing work: networks, identity, and environments that match how you ship.

Cost optimization

Evaluate the bill, then a comprehensive plan: resize, retire, and change what is expensive to run.