AI Lab · Production AI Engineering

AI that ships. AI that integrates. AI that earns its production seat.

The Core923 AI Lab builds and integrates production-grade AI systems for regulated enterprise. Generative, agentic, predictive, embedded — designed with the eval, observability, and governance that turn a clever demo into a system your team can actually run on a Tuesday.

Capabilities

Six AI capability surfaces.

Most AI work falls into one of these. Most engagements draw on three or four. We tell you which on the first call.

Agentic AI & Multi-Agent Systems

Production agents that reason, plan, and act — with tool use, memory, and guardrails. Single-agent assistants, multi-agent orchestrations, autonomous workflows. Built for safety and audit, not just clever demos.

LangGraphCrewAIAutoGenSemantic KernelOpenAI Assistants

Generative AI & RAG Systems

Retrieval-augmented generation with grounded sources, prompt engineering at scale, fine-tuning where it earns its keep. Open-weight (Llama, Mistral) and closed (GPT, Claude, Gemini). Hallucination defenses that actually work.

LangChainLlamaIndexvLLMPineconepgvector
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AI Engineering & MLOps Platforms

The platform layer beneath the models. Feature stores, training orchestration, model registries, deployment with shadow + canary, drift detection, eval harnesses. The boring infrastructure that lets data scientists ship.

KubeflowMLflowFeastRayTriton
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AI Integration Patterns

Adding AI to existing enterprise systems — not building greenfield AI products. Salesforce + Epic + SAP integrations with AI in the seam. API-first patterns, event-driven AI, AI-as-a-service for internal teams.

API GatewayKafkaiPaaSWebhooksSDKs
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AI Safety, Governance & Eval

The discipline that lets regulated industries deploy AI. Eval harnesses with statistical rigor, hallucination detection, bias monitoring, model cards, audit trails, kill switches. Compliance reviews don't surprise you.

Guardrails AINeMo GuardrailsSHAPOpenAI EvalsHelicone
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Vertical AI & Domain Models

Healthcare clinical AI, financial fraud and risk, telecom NOC intelligence. Not generic chatbots — domain models tuned for regulatory environments and the specific knowledge work done in your industry.

FHIR-awareHIPAAPCIClinical NLPRisk Models
Frameworks & Tooling

The modern AI engineering stack.

What we ship to production — chosen for fit, not vendor pressure.

Foundation Models & Inference

OpenAI / Anthropic / Gemini
Closed frontier models for capability ceiling
Llama / Mistral / Qwen
Open-weight for control + on-prem
vLLM / TGI / Ray Serve
Self-hosted high-throughput inference
Triton / Bedrock / Vertex AI
Managed inference at scale

Agentic & Orchestration

LangGraph
Stateful multi-step agent workflows
CrewAI / AutoGen
Multi-agent collaboration patterns
Semantic Kernel
Enterprise .NET / Python AI orchestration
DSPy
Programmatic prompt optimization

RAG & Vector Stores

LlamaIndex / LangChain
RAG pipelines + integrations
Pinecone / Weaviate / Qdrant
Managed vector databases
pgvector / Elasticsearch
Embedded vector in existing infra
Cohere Rerank
Retrieval quality refinement

MLOps & Eval

MLflow / Weights & Biases
Experiment tracking, model registry
Feast / Tecton
Feature stores for real-time ML
Helicone / LangSmith
LLM observability + debugging
Ragas / OpenAI Evals
Eval frameworks with rigor
Engagement Flow

From idea to production AI in 5 phases.

Not a PoC factory. We build to production from week one.

PHASE 01

Discover

Use case clarity. Data audit. Regulatory perimeter. Cost / accuracy / risk feasibility report.

PHASE 02

Prototype

End-to-end production-shape build on real data. Eval harness from day one. Real user feedback loop.

PHASE 03

Engineer

Pipelines, monitoring, model registry, deployment infra. Shadow before live. Cost ceilings at the gateway.

PHASE 04

Govern

Eval suite formalized. Bias / hallucination monitoring. Audit trails. Kill switches. Compliance review.

PHASE 05

Operate

30/60/90-day operate-with. Drift dashboards. Retraining cadence. Your team owns it by day 91.

Outcomes

What production AI looks like when it works.

Real numbers from recent engagements. Names anonymized.

31%
Fraud loss reduction

Tier-1 payments processor — real-time fraud scoring at P99 8ms latency, replacing a stalled rules engine.

2hr → 35min
Clinician documentation time

Large medical group — on-prem RAG with patient-context grounding. PHI never leaves the network. 87% draft acceptance.

$11M
Annual savings — customer ops

Tier-1 mobile carrier — fine-tuned encoder model for 47-category intent classification. Mis-routing 22% → 6%.

Why us

The senior bench AI requires.

Production from day one

No PoC theater. Every engagement ships to production within the first quarter — with eval, monitoring, and the operational discipline regulated industries demand.

Regulated by default

HIPAA, PCI, SOC 2, HITRUST aren't checkbox compliance — they're how we engineer. PHI never leaves trust boundaries. Audit trails are first-class. Kill switches always exist.

Honest about what AI can't do

Sometimes the right answer isn't AI. We'll tell you on the first call. We've turned down engagements where the problem was better solved by deterministic code, a domain expert, or a well-designed form.

Built to hand off

Operate-with phase from day 60. Your team owns the model lifecycle, the eval suite, the retraining cadence. We leave runbooks and capability — not dependency.

AI use case worth shipping?

30 minutes, senior ML engineer, no slides. We'll tell you on the first call whether it's worth shipping — and what it'll really cost.