Talos Foundry designs and builds AI agents that take on the manual, repetitive work running through your business — so your team moves faster, ships more, and spends less time buried in the tedious parts of the job.
Wherever the same work repeats every day or week, there's an agent we can build to run alongside your team.
Pull the numbers, build the recurring report, and surface what's worth a closer look — so the deck's ready before you've had your coffee.
Sort, draft, route, and follow up — the inbox stays under control and every reply is ready for you to send or tweak.
Briefs, first-draft content, scheduling, and performance rollups — the grunt work is done, you keep the creative calls.
Data entry, reconciliation, the copy-paste between tools — whatever glue work is eating your week, we build an agent to carry it.
A clear, low-risk path from first conversation to something that quietly works in the background.
We map your workflows and find where hours are quietly leaking out.
We design the exact agent workflow, tools, and guardrails needed.
We build and test against your real data before anything goes live.
We monitor, tune, and expand the system as your workflows evolve.
One system, built end to end and running in production. This is the shape the rest of this page is describing.
Monthly client reporting used to be a person opening every performance report, reading the numbers out into an email, and then remembering the follow-up tasks. Now a pipeline polls Gmail for each client’s report, has Claude read it against a fixed schema, drafts the client-ready summary, and files the follow-ups in the team’s project tool. A second pipeline runs the same shape for the other deliverable that goes out every month.
Nothing is auto-sent. Every draft sits in Gmail waiting on a human yes — the rule the rest of this page describes, applied to my own build first.
Interface redrawn for this page. Client names and figures are stand-ins.
The pipeline takes its dependencies by injection, so the business logic is unit-tested end to end without a single real API call. Tests fail on logic, not on someone else’s uptime.
Every scheduled job claims its work before doing it. A crash mid-run, or two runs overlapping, cannot email a client twice or file the same task again.
Database access starts closed and is opened row by row. A query without an explicit grant returns nothing — including a query nobody remembered to review.
What the model is allowed to trigger is a document, agreed up front, not an emergent property of the prompt. Anything outside it stops and waits for a person.
Three of the shapes this work usually takes. Yours will be its own thing — that is what the audit is for.
Someone exports from three systems, reconciles the numbers in a spreadsheet, and rebuilds the same deck before the week starts.
An agent pulls each source on a schedule, reconciles against last week, writes the summary, and flags the two figures that moved more than they should have.
A shared inbox takes a hundred-plus messages a day. Someone reads every one to find the dozen that actually need a person.
An agent classifies and routes on arrival, drafts replies to the repeat questions, and escalates the rest with the account history already attached.
Records get rekeyed by hand from one system into another. The typos surface weeks later, at month end, when they are expensive to unpick.
An agent watches for new records, validates them against your rules, writes both sides, and queues anything ambiguous for a human instead of guessing.
Nothing here needs a procurement cycle. Each stage stands on its own and earns the next one.
We walk through where your week actually goes. You leave with a written shortlist of the workflows worth automating, ranked by hours saved against effort to build.
One agent, one workflow, built and tested against your real data. We agree what success looks like in numbers before a line of code is written.
We monitor what is live, tune it as your process drifts, and add the next workflow when the last one has earned its place.
On pricing: every engagement is scoped and quoted in full before any work begins — a fixed fee for the pilot, a flat monthly rate after that. No hourly billing, no change-order games, no invoice you did not see coming.
No legacy playbooks, no bloated retainers, no game of telephone through account managers. You work straight with the people building your agents. Every engagement starts as a founding partnership — we learn your business, you shape how we build.
No account layers — you work directly with the people building your agents.
A working first agent in weeks, not a quarter of discovery decks.
Agents live inside the tools you already use — no new system to learn.
Early partners get direct founder attention at founding-client rates.
If yours is not here, put it in the form — a straight question gets a straight answer, not a call invitation.
Especially for you. The businesses with the most to gain are the ones where smart people spend hours a week on work a machine should be doing, because nobody has had the time to fix it. You do not need a technical team, a data warehouse, or an AI strategy. You need a process that repeats and someone who is tired of doing it.
No. A chatbot waits for you to paste something in and gives you text back. An agent runs on its own schedule, reads from the systems where your work actually lives, follows rules you defined, and hands off to a person when it hits something it should not decide alone. The model is one component. The value is in the plumbing, the guardrails, and knowing which decisions to keep human.
Nothing prepared. Bring the workflow that annoys you most and someone who actually does it day to day. If we go ahead, what we need from you is access to the relevant systems and about an hour a week during the build to check we have understood your process correctly.
No, and that is a deliberate constraint. Agents are built to work inside the systems you already have. Migrating your team to something new is a change project with its own failure modes, and it is not what you hired us for.
It will, occasionally, which is why the system is designed around that fact rather than around a promise it will not. Anything irreversible is queued for human approval instead of executed. Anything the agent is not confident about is escalated with its reasoning attached. Every action is logged, so when something looks off you can see exactly what happened rather than guessing. During the pilot we tune against your real cases until the error rate is one you are comfortable with.
Your data stays in your systems. Agents access it with scoped credentials you issue and can revoke without asking us. Where a workflow needs a language model, it runs against commercial APIs whose terms exclude business inputs from model training, and you get the specific provider terms in writing before you approve the design. If you have data residency rules or a vendor questionnaire, raise it in the audit and we will design around it.
You do. The workflows, the prompts, the configuration and the code we write for your engagement are yours. If you stop working with us, we help hand it over cleanly rather than holding it hostage.
A pilot is typically two to three weeks from kickoff to something live and doing real work. There is no lock-in at any stage. The audit is free and yours to keep, the pilot is a fixed fee with success criteria agreed before it starts, and ongoing work is month to month with no annual minimum.
That deserves a straight answer before you ask, not a policy page you have to go digging for. Here is how these systems are built.
Agents run against your systems using credentials you issue and can pull back at any moment, without calling us first. We never ask for a personal password, and we do not need to be the account owner.
Each agent gets the narrowest access that does the job and nothing spare. Read-only wherever reading is enough. Scoped to the folder, label, or table it needs — not the whole account.
Sending, paying, deleting, and anything else you cannot take back is drafted and queued for a person to approve. Autonomy gets extended to a specific action only once you have watched it behave.
Builds run against commercial model APIs whose terms exclude business inputs from model training. We will point you at the exact terms for whichever provider your system uses, in writing, before you approve it.
What the agent saw, what it decided, and what it did are logged where you can read them. When something goes wrong — and eventually something does — the answer is a lookup, not a guess.
Application security is a large part of my day job, not a page on a website — finding and fixing vulnerabilities, hardening auth and data handling, and closing the seams third-party integrations open up.
Have a specific requirement — a data residency rule, a vendor questionnaire, a restriction on what can leave your network? Raise it in the audit. It is far cheaper to design around than to retrofit, and if it makes a workflow a bad fit we would rather tell you then. Read the privacy policy for how this site itself handles what you send us.
Tell us about the workflow that never seems to end. We'll give you an honest read on whether an agent can take the weight off — no pitch, no pressure.
Not ready to talk? Take theautomation checklistinstead — ten questions that tell you which of your workflows is worth automating first. No email required.
