AI agents & agentic systems
We design and ship AI agents that operate like employees, chief of staff, ops manager, marketer, SDR, researcher, support, running 24/7 inside your stack. Agentic consulting for teams replacing or augmenting headcount, and a build practice that turns the roadmap into shipped systems.
Agentic systems are not chatbots. A chatbot answers a question and stops. An agent is given a goal, decides what to do next, calls tools, reads and writes to your systems, hands off to a human when it should, and keeps going until the work is done. That difference is what makes them useful as employees rather than as widgets. A chief of staff agent that reads your inbox, drafts responses in your voice, updates the CRM, and puts a shortlist on your desk at 8am is a fundamentally different thing than a helper bubble on a website. We build the second kind.
We work in two modes. Agentic consulting is where teams start when they know they need this but do not yet know what to build. We audit the org, map the workflows that are eating the most senior time, model the ROI of augmenting versus replacing versus keeping a role human, choose the tools and the stack, and produce a roadmap the team can execute against with or without us. Build is where we design, ship, integrate, monitor, and iterate the agents themselves, from single-purpose agents that automate one workflow to multi-agent systems that coordinate across a function.
The agent menu is broad on purpose. Chief of staff and executive assistant agents that run the inbox, calendar, and prep cycle. Operations and workflow agents that watch systems, catch exceptions, and route work. Marketing agents that draft, edit, and publish against a brand and content plan, run campaign ops, and iterate ad creative. Sales development agents that enrich, sequence, and follow up without dropping the ball. Research and analyst agents that read, summarize, and cite. Customer support agents that handle tier one and hand off cleanly. Recruiting, finance, and back-office agents that take the repetitive parts of the job and leave the judgment calls for the humans.
Under the hood we stay vendor-neutral. We build on the LLM providers and orchestration frameworks that fit the job, wire in retrieval and memory so agents actually know your business, and integrate against Slack, email, CRM, calendars, Notion and Drive, internal APIs, and browser automation where the work lives. Every agent ships with an evaluation loop, human-in-the-loop checkpoints where the stakes require them, guardrails against the failure modes that matter, and cost controls so the bill does not surprise anyone. Outcomes are framed in terms teams actually care about, headcount leverage, cycle-time reduction, coverage expansion, quality lift, not benchmark scores that never make it out of the deck.
What it solves.
- Hiring is slow, expensive, and still leaves senior time buried in repetitive work.
- The team wants leverage from AI but is stuck between demos, prompts, and hype with no roadmap.
- Coverage windows (nights, weekends, spikes) are broken because they depend on humans being awake.
- Existing AI tools are point solutions that do not talk to each other or to the actual systems the team runs on.
What ships.
- Agentic audit: workflow map, ROI model, and prioritized roadmap
- Agent design: role, tools, memory, guardrails, and eval plan
- Build and integration into Slack, email, CRM, calendars, Notion/Drive, and internal APIs
- Human-in-the-loop and approval flows for high-stakes steps
- Monitoring, evals, cost controls, and iteration cycle
- Team enablement so operators can extend and supervise the agents
Who it is for.
- — Founder-led teams trying to buy leverage instead of headcount
- — Lean ops and RevOps teams standardizing repetitive work
- — Agencies and studios who want senior output without linear hiring
- — PE-backed rollups standardizing back office across portfolio companies
- — Executives who want a chief of staff agent before they hire the human
The method.
Audit the work, then pick the agent
We start with the workflows, not the tools. What is eating senior time, what is on-call at midnight, what is the org afraid to hire for. That map decides which agents get built first and which stay on the roadmap.
Design for supervision, not autonomy for its own sake
Every agent has a role, a scope, tools it can call, and checkpoints where a human sees the work before it goes out. Autonomy is earned by the eval loop, not assumed on day one.
Ship into the stack you already run on
Agents live in Slack, email, the CRM, the docs, the calendar, the internal APIs. Not in a separate app the team forgets to open. Integration is where most agentic projects die and where we spend most of our time.
Instrument, evaluate, iterate
Every agent ships with evals, cost controls, and a monthly review that decides whether to expand its scope, tighten its guardrails, or retire it. Agents are software, not magic.
