Recommendation
Personalized product, content, and action recommendations driven by behavior and outcome signals.
Intelligent Systems
Software that learns, adapts, and decides.
Beyond chatbots: production platforms with intelligence woven into the data plane, the workflow plane, and the user experience.
Intelligence as a system property — not a feature.
When AI is bolted on, it ages badly. When it is part of the architecture — feeding the data plane, shaping decisions, learning from outcomes — it compounds. We build for the second case.
The pattern library we draw from
Prediction & forecasting
Demand, churn, fraud, capacity — quantified, time-bounded, and instrumented for accuracy tracking.
Anomaly detection
Real-time detection of operational and financial anomalies with low-noise alerting.
Classification & routing
Tickets, transactions, documents — automatically classified and routed with confidence scores.
Retrieval-augmented generation
Answers grounded in your documents, with citations and freshness guarantees.
Summarization & extraction
Long-form content compressed into operational artifacts: meeting notes, contract clauses, support trends.
How we architect intelligent platforms
Reliable data plane
Clean events, idempotent writes, time-travelable history — intelligence is downstream of data discipline.
Grounded models
RAG with vector stores, hybrid retrieval, and structured outputs — not free-form generation.
MLOps discipline
Model versioning, eval suites, A/B testing, rollback paths. The same discipline as the rest of the stack.
Human in the loop
Confidence thresholds, escalation paths, and feedback signals routed back into training data.
Built with
OAOpenAI
LCLangChain
VecPinecone / pgvector
PyPython
TFTensorFlow
LaLaravel
NdNodeJS
PgPostgreSQL
RdRedis
DkDocker