AI & MLOps
Build Production AI That Actually Ships
We take AI from a promising prototype to hardened, observable production. Agents, retrieval pipelines, and the MLOps backbone your system needs to stay accurate, cost-controlled, and reliable as usage compounds.
Demos are easy. Production is the hard part.
Almost every company now has an AI pilot. Far fewer have AI in production. The demo that wowed the boardroom tends to fall apart the moment it meets real users, messy data, awkward edge cases, a latency budget, and a finance team asking why the inference bill doubled overnight.
How we get you to production.
We start where the risk is highest. Before we write production code we define what good looks like in numbers (accuracy, latency, cost per request, and hallucination rate) and build an evaluation harness that measures it on every change. That harness becomes the contract: nothing ships unless it moves those numbers in the right direction.
Engineered to production standards.
- From proof of concept to production, with success metrics defined before we write a line of code
- Bedrock Agents for single & multi-agent architectures with custom tools and guardrails
- Advanced RAG using Snowflake Cortex, OpenSearch, and Kendra, with chunking, re-ranking, and eval harnesses
- Pipelines via LangChain, LlamaIndex, Haystack, and Strands
- MLOps with MLflow, Airflow, Kubeflow, and SageMaker
- LLM evaluation, prompt & version management, and drift / hallucination monitoring
- Fine-tuning, distillation, and model routing tuned for price-performance
- Inference cost & latency observability per model and route, with budget alerts and automatic fallback
“Faster time-to-value, lower inference costs, and AI you can audit and defend.”
Built for production from day one, then handed over with the runbooks so the capability stays with your team.
- 01Customer-facing assistants and copilots grounded in your own data
- 02Multi-agent workflows that take real actions behind guardrails
- 03Internal knowledge retrieval across documents, tickets, and wikis
- 04Rescuing a stalled proof of concept into a monitored production service
Battle-tested tools, chosen to fit your team and constraints, never technology for its own sake.
- Amazon Bedrock
- SageMaker
- LangChain
- LlamaIndex
- Snowflake Cortex
- OpenSearch
- MLflow
- Airflow
- Kubeflow
Runs on
Your cloud account, your racks, or the edge.See the infrastructure behind it
Why teams pick us for this.
- 01
Evaluation before deployment, always
We don't ship AI on vibes. Every system comes with an eval harness that scores accuracy, cost, and hallucination on each change, so quality is measured rather than hoped for.
- 02
Cost engineered in, not discovered later
Per-model and per-route observability, model routing, and budget alerts make your inference bill a design decision instead of a month-end surprise.
- 03
You own it when we leave
We build on your accounts with your engineers in the room, and hand over the runbooks, pipelines, and know-how so the capability stays in-house.
Answers before you ask.
We have a proof of concept that stalled. Can you take it to production?
That is the most common way clients come to us. We audit what exists, define the success metrics it was missing, and rebuild the parts that won't survive real traffic (evaluation, guardrails, observability, and cost controls) without throwing away the work that is already solid.
Do we have to use a specific model or cloud provider?
No. We are model- and vendor-agnostic. We recommend what fits your accuracy, latency, and budget targets, and design so you can swap models or routes later without a rewrite.
How do you keep AI from hallucinating or going off the rails?
Two ways. Grounded retrieval with re-ranking ties answers to your data, and guardrails plus continuous evaluation catch drift and bad outputs before your users do.
How long until we see something working?
We deliberately ship a focused, measurable proof of concept early, usually within the first few weeks, so you can judge the value before committing to the full build.
More of what we do.
Ready to build the future together?
Tell us where you're headed. We'll map the fastest secure path from idea to production.