Codiste Get something live

Right now it is answering somebody.

Codiste builds AI agents and keeps them serving. They run in FinTech, RegTech, PropTech and MarTech, for venture studios, funds and the founders they back. One of the products they run inside is our own, so we are on the receiving end of this as well.

Get something live Ask what it would take

In production

Four agents take real customer calls today. The number does not go up because a launch happened. It goes up when something stays up.

150+Systems shipped
5+Enterprise-grade logos
1Product we run ourselves
18Days to live traffic on our quickest voice deployment

Eight pieces ship together or not at all.

Give them to five vendors and the thing never goes live. It stays in integration.

Put a first release in

Nothing is real until strangers are using it.

A rehearsal has one user and that user built it. Real traffic brings people who do not know the phrasing, do not stop at the edge, and do not give up. The model keeps answering all the way through. It answers wrongly and it does so at full confidence.

Diligence lands on this and nothing else. An investor will not ask which model is underneath. They will ask what is live, how long it has been live, and who found out first the last time it was wrong.

Speed, leverage and risk. We are held to those three.

Speed

Weeks, not quarters. The quickest voice deployment we have run was taking real requests on day 18.

Leverage

Engineers who have kept agents serving before. You are not paying for the first time anyone did this.

Risk

Guardrails, evaluation and hallucination control go in before the traffic does, never after it.

Three competencies run behind anything live.

Artificial Intelligence

Architecture, guardrails and evaluation designed as one thing, so the system is dependable by construction and not by correction.

Blockchain Innovation

Decentralised applications that hold at scale, on secure and transparent ledgers keeping data whole across enterprise ecosystems. Supply chain transparency. Tokenisation.

Machine Learning

Forecasting through to hyper-personalisation, so an archive that has only ever been stored starts paying for the storage. Predictive analytics. Computer vision.

Four steps, and the fourth one never finishes.

The route is the same 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 in the first days, before anything is written.

  2. 02

    Prototype

    Your team gets something they can operate early. Opinions form against behaviour, not against a document.

  3. 03

    Launch

    It goes out hardened, guardrails enforced, audit trail writing from the first request onward.

  4. 04

    Iterate

    Real interactions feed the next revision. Tuning and retraining carry on for as long as it is serving.

Four agents are live.

  • 01

    Propizone CRM Voice AI

    Enquiries land from the portal at eleven at night. One is answered in eight seconds and the lead is qualified on the spot, where it used to sit in voicemail until morning.

    Eight seconds, drawn to length.

  • 02

    CandiPro ATS Voice AI

    Five hundred applicants used to mean five hundred screening calls. The agent runs the hiring manager's interview and sends back an ordered shortlist.

  • 03

    Neo-Bank Voice AI

    In a US neo-bank app, a voice layer takes account questions and moves the money, reading a confirmation back before any transfer clears.

  • 04

    ReachOut Voice AI

    ReachOut's agents ring back in seconds. The conversation happens while the person still wants it.

One arrangement covers every company in the fund.

Rates, priority access and delivery frameworks are agreed once and apply wherever your money is. We learn the thesis next to your partners, so a founder skips the vendor search and arrives at a first call already briefed.

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

Eight frameworks. All eight are met before anyone asks.

Data residency, PII handling, audit trails and explainability are decided in the architecture. A review meets a system that already complies, not a fortnight of work standing in front of one.

Why a fund keeps us on the other end of it.

Tell us what should be live.

Say what it does, what it sits inside, and when you need people using it. An engineer comes back with an approach, an effort range, and what would go out first.