Service · 02

AI & Automation

Transformative intelligence and autonomous workflow systems — designed to be safe, observable, and genuinely useful in production, not just a demo.

AI & Automation
80%
tier-1 tickets auto-resolved
<80ms
inference latency at scale
6 wk
from eval to production
100%
audited, reversible actions
What we deliver

Capabilities that ship to production

Scope a project

Custom models trained and served on your data, with monitoring and retraining pipelines.

Explore AI/ML Development
AI/ML Development

Task-scoped agents with tools, guardrails, and human-in-the-loop where it matters.

Explore AI Agent Development
AI Agent Development

Retrieval grounded in your knowledge base — chunking, embeddings, and evals done right.

Explore AI RAG Pipelines
AI RAG Pipelines

Content, code, and creative generation wired safely into your product surfaces.

Explore Generative AI Development
Generative AI Development

Event-driven automation that removes the repetitive 80% and escalates the rest.

Explore Workflow Automation
Workflow Automation

Low-latency speech interfaces for support, intake, and hands-free operations.

Explore Voice AI Development
Voice AI Development

Personalization engines that lift engagement and revenue, measured against a baseline.

Explore AI Recommendation Systems
AI Recommendation Systems

How an AI & Automation engagement runs

We de-risk before we build — a short evaluation phase proves the approach before anything ships to users.

.01

Evaluate

Prove the model on real data with a clear success bar before committing to build.

.02

Design & guardrail

Define scope, fallbacks, and observability so the system is safe and reversible.

.03

Build & integrate

Ship into your stack with tests, evals, and monitoring from day one.

.04

Operate & improve

Track quality in production and retrain as data and usage evolve.

A support agent that closes 80% of tier-1 tickets
Case study · Healthcare

A support agent that closes 80% of tier-1 tickets

A RAG-powered agent grounded in the client's knowledge base, with guardrails, evals, and clean human handoff when confidence drops.

Read the case study ↗
Tech stack

The tools we build with

Model-agnostic on purpose: the orchestration layer is built so a model swap is a config change, not a rewrite.

Models

AnthropicOpenAIHugging FaceMistralOllama

Orchestration

LangChainLangGraphTemporalAirflow

Retrieval & data

pgvectorQdrantPostgreSQLRedis

Evals & ops

Weights & BiasesOpenTelemetryGrafanaSentry

AI & Automation FAQ

We run a short evaluation phase against your real data with a success bar agreed up front. Sometimes the honest outcome is that a deterministic rule or a fixed integration solves it more cheaply, and we’ll say so.

We’re model-agnostic — frontier APIs or open-weight models hosted in your environment, chosen per use case for cost, latency and data residency. The orchestration layer is built so swapping models is a config change, not a rewrite.

No. We use enterprise endpoints with training opt-out, or host open-weight models inside your own infrastructure where data residency demands it. Which one we pick is a decision we make with you, not for you.

Scoped permissions per action, explicit guardrails, evaluation suites that run on every change, and full logging so anything automated can be audited and reversed. Nothing ships that can’t be rolled back.

A scoped system typically goes from evaluation to production in six to eight weeks. The eval phase is deliberately short and cheap so you can stop before the expensive part if the numbers don’t hold up.

Our work

Related work

All work

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