Working Agents · For Regulated Funds
We ran agentic AI inside a leading hedge fund. Now we build working agents inside yours.
The full factory inside your perimeter in two weeks — turn-key if you have no infrastructure at all. Your people build workflows in plain language; when a system calls for engineers, we co-develop it, guaranteed.
Claim your first seatThe systems your team always wanted, finally built.
Every fund keeps a quiet backlog: tools the desk asked for years ago, still waiting behind whatever internal engineering had to do first. We put frontier intelligence beside the people who own those processes, co-creating until the backlog moves.
aCapital formation
LP pipelines researched and kept warm, dossiers ready before every meeting, DDQs and data-room requests handled overnight. Partners show up to close.
bResearch & deal flow
Every filing, transcript, and data room in your universe read overnight and scored against your thesis. First drafts arrive with citations; analysts start at the interesting part.
cQuant & data ops
Vendor feeds onboarded, validated, and watched. Backtests run and written up, anomalies investigated before they touch a signal. Quants stay on alpha.
dMarkets & treasury
Breaks, fails, margin calls, and covenants worked overnight across admins and prime brokers. Exceptions reach a person with the evidence attached.
eCompliance reporting
Form PF, Annex IV, and 13F assembled from the book, every number traceable to source. Marketing review and personal-trading surveillance run continuously; sign-off stays with your CCO.
fInvestor relations
Quarterly letters drafted in your voice from your numbers, LP queries answered same-day, KYC refresh queued for sign-off. The relationship time stays with the partners.
Built for multifamily offices, private equity, and hedge funds, front office to back. What ships is the system your team designs — and the hours come back to the people whose judgment is the business.
Experience it first. Expand by the seat. Co-develop what's heavy.
01 · Experience
On us
The full harness, deployed for one principal. Brief the Chief of Staff, build your first workflows yourself — feel it firsthand. Converts to your first principal seat.
02 · Expand
from £1,500
Principal seat £3,500 — the chief of staff, priority support. Team seat £1,500 — process owners self-developing in the factory. Operation, evals, and upgrades included; the brain compounds across seats.
03 · Co-develop
from £75,000
Our engineers embed to build the heavy production systems with your team. 50% back if it isn't live.
- Stack
- Claude-first, with private open-weight models for role-specific sub-agents. Your cloud, inside your security perimeter.
- No infrastructure?
- Turn-key deployment: we provision a dedicated single-tenant environment in your name — your account, your keys, our runbooks. Infrastructure billed at provider cost, itemised on the Ledger.
- Model spend
- Billed at provider cost, itemised per task in your Ledger.
- Ownership
- Your workflows and data are yours outright. The Genba harness carries a perpetual license for the deployed version, so it keeps running with or without us. What your teams build in the seats — the capabilities and the record — compounds as your asset, which is what makes leaving safe.
Genba (現場) is where the work actually happens: the desk, the book, the close. A craftsman is judged by what still runs after he leaves.
Most enterprise AI is sold from a slide and dies on contact with a real operation. Our engineers embed where the work happens and stay until an agent runs there in production.
We install a software factory. Your people run the line.
Your first seat puts the whole harness in place — gateway, ledger, evals, company brain. The first workflow is the first thing off the line, and that's how a backlog actually clears: the cost of building collapses, and it stays collapsed.
- Briefed in plain language. The process owner briefs the factory the way they'd brief a new hire. Agents draft, build, and test inside role-based access, approval gates, and the Ledger's audit trail.
- Ownership drives adoption. People champion what they helped build. The fear of being replaced fades when the agent answers to you.
- Every build starts further ahead. Workflow two reuses the gateway, the audit, and the evals of workflow one. The second build is faster than the first; the fifth barely resembles a project at all.
Engineered to the standard a regulated fund demands. Every action is gated and recorded; people hold the decisions that carry consequences.
- Sandboxed and secret-free. Agents hold no credentials. The Gateway grants scoped, policy-checked access and escalates to a person when the stakes require it.
- Audited to the token. The Ledger ties every action, inference, and dollar of model spend to the task that caused it. An audit becomes a query.
- Humans hold consequence. Anything with stakes routes to a person, with the agent's reasoning visible enough to challenge.
- No shadow automations. Every agent-built capability is registered, versioned, and held to evaluation thresholds. Query the registry: what exists, who owns it, what it can access, how it performs.
- Watched from outside. Sentinels the agents cannot see stand watch. Security reads every log stream for unapproved behaviour — intentional or not — with freeze and kill-switch authority. Compliance screens every outbound flow, anonymising PII and blocking flagged content. Cost watches the Ledger and freezes budget runaways. All escalate to human triage.
The company brain is the institutional memory every agent reads from and writes back to, with provenance built in.
Each finished task leaves the firm knowing a little more, and the knowledge stays when people move on. The agents are outputs; the asset is the institutional intelligence you accumulate — owned by you, exported on exit, appreciating as models commoditise.
A Chief of Staff — itself an agent — is briefed through the front doors your people already use: Slack, Teams, email. It works a shared task database in parallel and routes every task to the right mind for the job — role-specific agents on open-weight models you own, or the frontier when the work demands it. Nothing consequential leaves the system without passing the approval gate, and every send lands in the audit log. Your data stays inside the perimeter.
The open-weight models are yours, deployed inside your perimeter and improving over time — RLVR fine-tuning and eval-driven prompt optimisation, per agentic role. The intelligence your operation accumulates is an asset you own outright, immune to vendor lock-in. The same gateway, ledger, and sentinels govern every route, so a regulator sees identical controls whichever model served the request. On the outbound path, the compliance sentinel screens every flow with locally hosted models of its own: PII is anonymised before anything crosses the boundary, and anything compliance-flagged is blocked and escalated to a person.
Research, end to end — a multi-agent harness inside your perimeter. One evening, one analyst, one structured note by morning.
An analyst briefs the harness: the target, the thesis memo, the questions that actually matter.
The harness fans out — one agent reads the data room and filings, one runs the quant work.
The heavy reading runs on open-weight models on your hardware. The data room never leaves.
One structured note: scored thesis map, quant appendix, contradictions flagged.
The team challenges it in plain language; answers come back with sources attached.
Documents read, models used, the lineage of every number: recorded per task.
The same pattern runs trading (signal to settlement, gated and booked) and investor relations (a 240-question DDQ returned the same day, signed by people).
Two models. One control plane.
For principals: a chief of staff. Arrive Monday to find the night's work done — the investor letter drafted, the overnight moves reconciled, the follow-ups queued for a yes or a no. Every engagement starts here: one seat, one principal, the fastest way to feel what delegating to an agent is like.
For the divisions: teammate agents. Inside each team, working the routine alongside the people who own it — fails and breaks worked before the desk sits down, filings read overnight, DDQs drafted from the approved library. Division-scoped access, the same controls throughout.
We build inside Anthropic's ecosystem, on the frontier of what Claude can safely do in production.
- Claude Partner Network candidate — Anthropic's services partner programme.
- Claude Certified Architect — credential path in progress.
- Claude-first by design; model-aware where a deployment calls for it.
You work directly with the people who build it.
Makoto Tominaga
Production AI · Funds
Two years running production agentic AI inside a leading hedge fund. Twenty-five years across kernel, security, and AI: AuthenTec (acquired by Apple), Validity Sensors (acquired by Synaptics), founder of Credify (BEENEXT and DEEPCORE-backed).
Alex Norris
Investments · Quant
Head of Investments at the same fund, risen from quantitative researcher to Director. MSc in Risk Management & Financial Engineering from Imperial College London; first-in-cohort MSc in Data Science at Bath. He has run the research the agents now serve.
Steve Lim
Engineering · Fund Systems
Head of Engineering at the same fund. The production and data infrastructure behind a decade of award-winning performance is built and operated by his team.
Toan Nguyen
Delivery · Engineering
CEO of Trustify Technology (Vietnam). Fifteen years of enterprise IT delivery at Nortel, SingTel, Ruckus Wireless and Absolute. Runs an established engineering organisation with managed-services discipline and Southeast Asian cost economics.
Tell us what's sat on your backlog the longest.
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