AI that actually ships.
We bridge the gap between research and revenue with battle-tested infrastructure, model-agnostic pipelines, and engineering rigor.
PoC to Production
Most AI projects die in notebooks. We ship to production with monitoring, evals, and rollback safety from day one.
Model-Agnostic
OpenAI, Anthropic, open-source, fine-tuned — we pick what fits your latency, cost, and compliance requirements.
Compliance-Ready
Audit logs, PII redaction, and governance built in. EU AI Act, NIST AI RMF, SOC 2 — we speak the language.
Cost-Aware
Token budgets, semantic caching, and intelligent model routing for sustainable AI economics at any scale.
The full AI stack.
From retrieval to reasoning, from training to telemetry — we cover every layer of modern AI systems.
RAG & Retrieval Architecture
Production-grade retrieval pipelines that go beyond naive embedding search. We design for accuracy, latency, and grounded responses at enterprise scale.
- Vector databases: Pinecone, Weaviate, Qdrant, pgvector
- Embedding model selection & evaluation
- Hybrid search (dense + sparse / BM25)
- Reranking pipelines (Cohere, cross-encoders)
- GraphRAG / knowledge graph augmentation
- Multi-modal RAG (text + images + tables)
LLM Ops & Inference Infrastructure
The plumbing that keeps AI systems reliable, observable, and economical in production. Treat your LLMs the way you treat your APIs.
- LLM gateways & multi-provider routing with failover
- Prompt versioning, A/B testing & eval pipelines
- LLM-as-judge & golden dataset regression testing
- Self-hosted inference: vLLM, TGI, Ollama
- Token observability & FinOps for AI workloads
- Semantic caching & request deduplication
Agentic Systems
Multi-step, tool-using agents that take real actions in real systems — with guardrails, memory, and human oversight where it matters.
- Multi-agent orchestration (LangGraph, CrewAI, custom)
- Tool use & function calling architectures
- Agent memory: short-term, long-term, episodic
- Human-in-the-loop workflows & approval gates
- Agent evaluation & guardrails
- Stateful execution & checkpointing
Fine-tuning & Customization
When prompting isn't enough, we fine-tune. From parameter-efficient adapters to full alignment workflows for domain-specific accuracy.
- LoRA / QLoRA parameter-efficient fine-tuning
- Domain-specific embedding models
- Synthetic data generation for training
- RLHF / DPO alignment workflows
- Continued pretraining for vertical domains
- Quantization & inference optimization
Data & Pipelines
AI is only as good as the data that feeds it. We build the ingestion, transformation, and serving infrastructure that makes models reliable.
- Feature stores (Feast, Tecton)
- Vector pipelines: chunking, embedding, indexing
- Real-time vs batch inference architectures
- Data lineage & governance
- Streaming ingestion with Kafka, Kinesis
- Lakehouse integration (Databricks, Snowflake)
Safety & Governance
Compliance isn't a checkbox — it's an architecture. We bake safety, observability, and audit trails into every layer of the stack.
- Guardrails & content moderation pipelines
- PII detection & redaction
- Model versioning & rollback
- Audit logs & compliance reporting
- EU AI Act, NIST AI RMF alignment
- Red-teaming & adversarial testing