When the workflow doesn't fit a product, we build the system.
Agentic workflows that use your tools. Copilots that live in Slack and read your CRM, your email and your documents. Cameras turned into structured signal. Content engines on a cadence. Designed, built, evaluated and run by senior engineers, in your environment, on your data.
The problems worth solving are shaped like you.
Off-the-shelf AI products are good at generic jobs. The expensive workflows in a real business are rarely generic: the deal desk that spans a Slack channel, a CRM record, an email thread, a signed contract and a shared folder; the production line where the defect is specific to your product; the marketing calendar that needs your brand, not a template. Those are systems, and they have to be engineered.
We build them the way production software gets built: a written design you can interrogate, an evaluation set before the first prompt, guardrails on what the system may and may not do, versioned releases, and monitoring once it is live. The same senior team from the first call to production, and no junior hands on the keyboard.
What we build.
- Agentic workflows. Orchestrator agents with tool use across your systems, bounded by iteration limits, permissions and human approval steps where the action matters. Tailored AI systems workshop →
- Internal copilots. Slack-resident assistants that answer from the CRM, email, contracts and documents with citations, draft the deliverable, and never send without a person.
- Computer vision and anomaly detection. Object and defect detection, OCR and document parsing, people counting, safety and intrusion monitoring, on-device or in the cloud. Computer vision → · Anomaly detection →
- Generative content engines. Product, social and ad video from a written brief, avatar and spokesperson video in any language, always-on calendars scripted by an AI editor. Generative video →
- LLM applications and fine-tunes. Retrieval over your data, custom fine-tunes where they earn their keep, and model choice per workload.
- Evals, guardrails, monitoring. A held-out test set, prompt versioning, tracing and cost tracking, so you can see what the system did and why.
- Integration into your stack. Slack, Gmail, Google Drive, e-signature, CRM, ERP, telephony, whichever combination your operation actually runs on.
Built on.
- Claude
- GPT
- Gemini
- DeepSeek
- LangGraph
- Pinecone
- Langfuse
- YOLO
- Roboflow
- Postgres
- Next.js
- your stack
Model choice is per workload and reversible. Deployment is cloud, hybrid or on-premise. The code, the prompts and the evaluation sets are documented and handed over.
An AI deal advisor that reads everything about a deal and answers in Slack.
One mention in a deal channel pulls context from Slack, the CRM, Gmail, e-signed contracts and Drive, answers in the right role, and drafts the document for a human to send.
Read the case study →- Systems
- Agentic copilot
- Sources joined
- 5
- Built with
- Claude, Slack, Podio, Gmail, Drive
Where it pays back first.
Deal desks and transaction teams
One question in the deal channel, answered with the full context across CRM, email, contracts and files, in the legal, financial or sales role the question needs.
Manufacturing and warehousing
Defects caught in-line before shipping, safety violations flagged with the frame attached, counts and compliance from the cameras you already own.
Multi-location operators
Cross-branch reporting, exception flagging and a copilot that knows every location's numbers.
Marketing teams
Branded video and copy variants on a cadence, A/B-ready, from a brief instead of a shoot day.
Professional services
Internal copilots over case files, engagement letters and correspondence, with citations and draft-only writes.
Founders with a specific idea
The AI system you wish you already shipped, designed, evaluated and built to production grade.
How a build runs.
- Scope (week 1). A strategy call with a principal engineer. We map the system, surface the risks, agree the success metrics and quote it in writing within a week.
- Design (week 2). Architecture, data flow, model choices, evaluation plan and guardrails in a short written design doc you can interrogate before any code is written.
- Build and ship (weeks 3–12). Versioned releases, real metrics, weekly demos in your own environment. Founding clients get the first prototype free, on their own data.
- Tend (onward). Monitoring, evals, retraining and second-generation builds under a partnership, or a documented handover to your team.
Frequently asked questions.
Do we own the system?
Yes. It is built in your accounts and your environment; the code, prompts, evaluation sets and documentation are handed over. If we part ways, everything keeps running.
Which models do you use?
Whichever fits the workload: Claude, GPT, Gemini, DeepSeek, or open models where data residency demands it. Model choice is a configuration, not a rebuild.
How do you keep an agent from doing something it shouldn't?
Explicit tool permissions, iteration limits, draft-only writes for anything outward-facing, human approval steps, and evals that run before every release.
What does it cost?
Three shapes: a two-week paid discovery, a fixed-scope build, or a monthly partnership. Written scope and a fixed-fee quote before work begins.
Tell us the system you wish you already shipped.
A 30-minute strategy call with a principal engineer is the only place to begin.
Book a strategy call →