Solutions that turn AI and data into reliable production capabilities
— streaming, lakehouse, and LLM systems built for real operations
We deliver end-to-end solutions across streaming, lakehouse/analytics, reliability programs, and LLM systems — including automation (n8n) and operating models that keep them stable.
Talk to an engineer Request a solution fit session
01
AI Foundry & LLMOps
RAG, evals, guardrails, monitoring, feedback loops
02
Streaming & Real-time Analytics
Kafka + processing + serving patterns
03
Data Trust & Governance
contracts, DQ, lineage, incident reduction
Every solution includes architecture, implementation, and operational ownership
We don't stop at "it works." We deliver SLOs, dashboards, runbooks, and a clear operating model that survives production change.
Architecture blueprint + ADRs
Validation plan + tests + quality gates
Observability + SLOs + incident playbooks
Security/governance patterns
Automation workflows (n8n) where they reduce manual effort and risk
Why work with us
Six pillars that define how we deliver production systems
01
AI Foundry (continuous AI delivery)
Build a repeatable pipeline for AI value with governance and measurable quality.
  • prompt/config versioning
  • eval gates
  • feedback loops
  • cost controls
02
RAG & Knowledge Systems
Retrieval quality, grounding, traceability, and privacy controls.
  • chunking strategy
  • indexing
  • access control
  • citations/trace IDs
03
Streaming & Event Processing
Production streaming with contracts, replay, and deterministic reprocessing.
  • schema registry
  • idempotency
  • DLQ/quarantine
  • load testing
04
Real-time Analytics & Serving
Low-latency pipelines and serving layers for decisions and products.
  • latency budgets
  • aggregation patterns
  • real-time storage strategy
05
Data Trust & Quality Program
Reduce incidents and improve trust with engineering discipline.
  • DQ checks
  • anomaly monitors
  • lineage
  • ownership
  • SLAs
06
Automation & AI Ops (n8n)
Automate operational work around AI/data with auditable workflows.
  • incident workflows
  • approval gates
  • reporting
  • CRM integrations
Our delivery process
A proven approach to building production systems
01
Step 1 — Use case & metrics
define outcomes (latency/freshness/quality/cost)
02
Step 2 — Architecture alignment
blueprint, contracts, integration approach
03
Step 3 — Delivery
build + tests + observability + automation workflows
04
Step 4 — Operate
SLOs, runbooks, incident workflow, continuous optimization
Request a solution fir session
Roles that deliver these solutions
Streaming Engineer (Kafka + Processing)
Builds reliable event pipelines with replay, idempotency, and observability.
Core skills
Kafka, Flink/Spark, schema evolution, backpressure patterns
Production focus
consumer lag, latency, incident debugging, load tests
View profile
Automation Engineer (n8n + Platform Workflows)
Builds audited automations for data/AI ops that reduce manual work and MTTR.
Core skills
n8n, webhooks, APIs, Slack/Jira/CRM automations, retries/approvals
Production focus
safe execution, audit logs, rollback patterns, observability hooks
View profile
Engagement models
Flexible approaches to match your needs
01
Solution Fit Session + Delivery Blueprint
Best for
new projects, migrations
Includes:
architecture review + roadmap + validation plan
02
Delivery Squad (Build + Run)
Best for
full implementation + operations
Includes:
engineers + governance + SLOs + continuous improvement
03
Stability & Cost Sprint
Best for
incidents, cost reduction
Includes:
quick wins + runbooks + monitoring
Use cases
Real-world applications we've delivered
RAG assistant for support/ops teams with measurable deflection and quality
Streaming ingestion + real-time dashboards for operational decisions
Data trust program to reduce broken reports and failed pipelines
n8n automation of incident workflows and executive reporting
Warehouse/lakehouse and streaming compute cost optimization with predictable scaling
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