Codiste Tell us what it must never do

Every agent needs something it cannot get past.

Interlock

A guard that works is one nobody notices. You do not watch it stop things. You simply never find out what would have happened.

Codiste builds AI agents for venture studios, funds and the founders they back, across FinTech, RegTech, PropTech and MarTech, and we build the bound before we build the behaviour.

Tell us what it must never do Ask how the bound is set
150+Systems shipped
5+Enterprise-grade logos
1Product we run ourselves
18Days to live traffic on our quickest voice deployment

Eight disciplines, all of them inside the same rail.

Hand them to five suppliers and the bound stops at each contract boundary, which is exactly where the awkward behaviour turns up.

Scope a first release
  • 01Strategy
  • 02Architecture
  • 03Retrieval
  • 04Orchestration
  • 05Guardrails
  • 06Evaluation
  • 07Deployment
  • 08Observability

The failure is never the model deciding to lie.

It was asked something nobody anticipated, nothing in its construction said no, and it produced a fluent answer because that is the only thing it knows how to produce. Discouraging that in a prompt is not a bound. It is a request.

Diligence arrives at the same question from the other side. An investor wants to know which actions are impossible rather than which are discouraged, and who can change that list without anybody noticing.

We answer for speed, leverage and risk.

Speed

The unit is a week and not a quarter. Our fastest voice deployment was carrying live requests by day 18.

Leverage

Engineers who have set these bounds before, so you are not funding the first attempt at it.

Risk

Guardrails, evaluation and hallucination control are structural, never a later pass.

Three competencies, bounded the same way.

Artificial Intelligence

Architecture, guardrails and evaluation drawn as one piece of work, so what the system will not do is fixed in the same place as what it does.

Blockchain Innovation

Decentralised applications that carry real load, on secure and transparent ledgers holding data intact across enterprise ecosystems. Supply chain transparency. Tokenisation.

Machine Learning

Forecasting through to hyper-personalisation, so an archive that has sat untouched for years begins to pay for the space it occupies. Predictive analytics. Computer vision.

Four steps, and a rail at every one.

The same route for a seed-stage voice product and for a Series C platform putting agents into a core system.

  1. 01

    Discover

    Product, data and every decision the agent will own are settled first, along with the list of things it will be unable to do.

  2. 02

    Prototype

    Your team gets something they can push at early, which is the only honest way to find where the bound is in the wrong place.

  3. 03

    Launch

    It ships hardened, with the bound enforced in the architecture and an audit trail running from the first request.

  4. 04

    Iterate

    Real traffic shows where the rail sits too tight or too loose, and it is moved deliberately rather than quietly.

Four agents, each one running inside a bound.

01

Propizone CRM Voice AI

A property enquiry arriving late at night once waited in voicemail until somebody opened the inbox. It is answered in eight seconds and qualified on the call.

02

CandiPro ATS Voice AI

Five hundred applicants used to mean five hundred screening calls against one recruiter's calendar. The agent runs the hiring manager's own interview and returns an ordered shortlist.

03

Neo-Bank Voice AI

In a US neo-bank application a voice layer takes the account question and moves the money, and it reads a confirmation back before any transfer is allowed to clear.

04

ReachOut Voice AI

ReachOut's agents call back within seconds, catching the person while the thing they enquired about is still on their mind.

One agreement, and the same rail around every company you back.

Rates, priority access and delivery frameworks are settled once at fund level and apply wherever your capital sits. Your partners brief us on the thesis once, and a founder arrives at a first call without having to explain it again.

  • FinTech
  • RegTech
  • PropTech
  • MarTech
  • SaaS
  • AdTech
  • SportsTech

Eight frameworks, and the rail is drawn to all of them.

Data residency, PII handling, audit trails and explainability are decided in the architecture, so a review meets a system already inside the line rather than a fortnight of work to get it there.

  • SOC 2
  • ISO 27001
  • GDPR
  • HIPAA
  • EU AI Act
  • FINRA
  • PCI DSS
  • CCPA

Why a fund wants the rail built in.

01

Studio velocity

Engineers who already know where production agents wander, so the early weeks go on the build.

02

Cross-stack fluency

A portfolio spans many stacks and so do we: voice, LLM, agentic, retrieval, edge, and the legacy system still doing the work.

03

Reliability as discipline

Guardrails, evaluation and hallucination control sit in the structure, not in a review before launch.

04

Investor-grade delivery

A round and a reputation ride on the outcome, so the work is done as though our name sat beside yours.

Tell us what your agent must never do.

Say what it does, what it sits inside, and the one action that would be unacceptable. An engineer replies with an approach, an effort range, and where the bound would go first.