Platforms we build, modernize, and operate
— streaming, lakehouse, and LLM systems built for real operations
— as production products
We treat platforms like internal products: reference architectures, golden paths, reliability standards, and automation around operations (n8n + CI/CD). This is not a logo wall — it's a production playbook you can execute.
Request a platform blueprint Ask about your stack
01
Streaming Platform
event contracts, schema evolution, replay, observability
02
Lakehouse/Analytics Platform
Iceberg/Delta, transformation/testing, governance
03
AI Platform
RAG/agents, eval harness, guardrails, monitoring, cost controls
Platform engineering with operational maturity
Every platform includes build + run: SLOs, dashboards, runbooks, incident workflow, and automation to reduce manual work and operational risk.
Standardized environments and IaC
CI/CD for data + services + prompts/config
OpenTelemetry observability
Governance and access controls
n8n automations for ops workflows
Why work with us
Six pillars that define how we deliver production systems
01
Streaming Platform Foundation
Core infrastructure for event-driven architectures.
  • topic taxonomy
  • schema registry
  • consumer patterns
  • DLQ/quarantine
  • replay tooling
02
Processing & Orchestration Layer
Reliable transformation and workflow management.
  • orchestration
  • backfills
  • retry semantics
  • dependency management
  • data tests
03
Lakehouse/Analytics Core
Modern analytics with performance and governance.
  • Iceberg/Delta design
  • partitioning
  • compaction
  • query engine
  • ssemantic layer patterns
04
Data Trust & Governance
Quality and ownership at scale.
  • contracts
  • DQ checks
  • lineage
  • ownership
  • freshness SLAs
  • incident workflow
05
AI Platform (LLMOps / RAG / Agents)
Production AI with controls.
  • retrieval pipelines
  • eval harness
  • guardrails
  • monitoring
  • privacy cont
  • rolsrollout strategies
06
Automation Layer (n8n)
Operational efficiency through automation.
  • approvals
  • incident flows
  • reporting
  • CRM integration
  • audit logs
  • safe retries
Our delivery process
A proven approach to building production systems
01
Step 1 — Current platform scan
architecture, bottlenecks, risks, cost drivers, reliability gaps
02
Step 2 — Target platform blueprint
reference architecture, standards, ADRs, operating model
03
Step 3 — Implementation & enablement
build, instrument, automate, document, train
04
Step 4 — Operate & optimize
SLO cycles, incident reduction, cost/performance improvements
Request a platform blueprint
Platform-focused engineers
Data Platform Engineer (Cloud-Native)
Builds golden paths, CI/CD, IaC, and platform standards for data teams.
Core skills
Kubernetes, IaC, GitOps, IAM, observability
Production focus
reliability, change safety, enablement
View profile
Data Architect (Platform Blueprint)
Designs reference architectures, governance, and target operating models.
Core skills
domain modeling, lakehouse/warehouse, security, cost governance
Production focus
alignment across teams, scalable standards
View profile
Engagement models
Flexible approaches to match your needs
01
Platform Audit (2–3 weeks)
Best for
assessment and roadmap
Includes:
findings + recommendations + prioritized plan
02
Platform Build Squad
Best for
full platform implementation
Includes:
engineers + architecture + governance + enablement
03
Build–Operate–Transfer
Best for
long-term ownership transfer
Includes:
build + run + documentation + training
Use cases we solve
Real-world applications we've delivered
Build a streaming foundation with safe replay and schema evolution
Modernize lakehouse tables for performance and cost control
Add governance and reliability gates to reduce data incidents
Enable LLM/RAG platform with eval and guardrails
Automate ops workflows with n8n
n8n-driven ops automations: incident workflows, reporting, approvals, governance actions
Frequently asked questions
Are you a staffing marketplace?
Do you build "AI agents"?
How do you prove AI quality?
How do you prevent data incidents?
Can you integrate n8n with our stack?
Want production-grade AI and
data platforms — not fragile demos?
Share your current architecture and goals. We'll return with a risk map, target blueprint, anddelivery plan.
Book a technical call Request a platform assessment
Production AI & Data Platforms — streaming, lakehouse, and LLM systems built for real operations.
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Production-grade AI & Data engineering