Turn your proprietary data into an unfair advantage.
We take large language models, machine learning, and automation out of the demo stage and wire them into the workflows, data, and permissions your company already runs on.
AI pilots stall the moment they meet real data.
The model demo impresses the board, then collapses against messy records, access rules, and a workforce that doesn't trust the output.
How we deliver, sprint by sprint
Opportunity audit
We map your workflows to find where AI removes measurable hours, and just as importantly where it shouldn't be used at all.
Ground the model in your data
Ingestion, chunking, embeddings, and retrieval built against your real corpus, with permissions inherited from your existing roles.
Evaluate before you trust
A golden dataset and automated eval suite gate every prompt and model change in CI, so accuracy is measured, not assumed.
Embed and monitor
The capability lands inside the tool your team already uses — CRM, ERP, help desk — with cost, latency, and quality dashboards attached.
Built as a bento of production-ready capability
LLM copilots
Assistants scoped to a job function, grounded in your documents and permissions.
RAG pipelines
Vector and hybrid search over contracts, tickets, wikis, and product data.
Workflow automation
Document intake, classification, and routing that eliminates queue work.
Custom ML models
Forecasting, scoring, and anomaly detection trained on your own history.
Governance & privacy
PII redaction, tenant isolation, prompt logging, and full audit trails.
Cost & latency control
Model routing, caching, and budgets that keep unit economics sane at scale.
The stack behind the work
OpenAI & Anthropic
Frontier models routed per task for the right cost-quality tradeoff.
LangChain & LlamaIndex
Orchestration for retrieval, tools, and multi-step agent workflows.
pgvector & Pinecone
Production vector search alongside your relational data.
Python & PyTorch
Custom model training, fine-tuning, and evaluation pipelines.
AWS Bedrock & SageMaker
In-VPC inference for regulated and data-sensitive workloads.
LangSmith
Tracing, eval scoring, and regression detection on every release.
Three ways AI earns its place in production
Custom LLMs & RAG
Stop using generic AI. We build custom Retrieval-Augmented Generation models trained exclusively on your secure enterprise data.
- Hybrid vector and keyword retrieval over contracts, tickets, wikis, and product data
- Answers cited to source documents so every claim is verifiable
- Permission-aware retrieval that respects the access rules you already enforce
Workflow Automation
Autonomous agents that execute complex back-office tasks — intake, classification, routing, and reconciliation — without a human babysitting a queue.
- Document intake and extraction with human review only on low-confidence cases
- Tool-using agents wired into your CRM, ERP, and ticketing systems
- Deterministic guardrails and rollback on every write operation
Legacy System Modernization
Injecting modern machine learning into legacy databases — forecasting, scoring, and anomaly detection on the operational data you already have.
- Change-data-capture pipelines out of mainframe and on-prem SQL systems
- Forecasting and risk scoring served back through APIs your legacy UI can call
- No rip-and-replace: the system of record stays exactly where it is
Zero Trust by default
Your data never trains someone else’s model.
Every deployment runs under Zero Trust principles: tenant-isolated vector stores, PII redaction before inference, least-privilege service identities, and full prompt and response audit logs. Every answer is grounded in retrieved source documents and cited back to them, so the system says “I do not know” instead of inventing one. Prompt and model changes ship only after passing an automated evaluation suite scored against your own ground-truth set.
Measured hours returned, not a science project.
Every AI engagement is scoped against a metric — review time, resolution rate, forecast error — and we report against it after launch.
- Manual review and triage time cut by half or more on targeted workflows.
- Grounded answers with citations your team can verify instantly.
- Automated evals blocking accuracy regressions before production.
- Data governance documentation your security reviewers accept.
- Per-request cost visibility with budget guardrails enforced in code.
Delivered by 100+ engineers in Shelby Township, MI. Call 313-476-3234.
Ready to scale your digital infrastructure?
Book a free technical discovery call with our engineering team. You will talk to an engineer who has shipped systems like yours — not a salesperson reading a script.
100+ Engineers · Shelby Township, MI · 100% US-Based