Codiste Take us through the load

We build agents with room left above the line, so the first real hour is not the hour they give way.

Codiste designs, ships and runs AI agents for venture studios, funds and the founders they back. Work goes live across FinTech, RegTech, PropTech and MarTech, sized for the hour real customers arrive rather than the hour of the rehearsal.

Take us through the load Put a number on it
150+Systems shipped and still carrying traffic
5+Enterprise-grade logos
1Product we run ourselves
18Days to live traffic on our quickest voice deployment

One team holds all eight parts of the stack.

Split them across five vendors and the queue forms at the handover, every time.

Size a first release

A demo runs one request at a time. Customers do not queue politely.

Five people clicking through a rehearsal is not load. Real traffic arrives together, and the agent keeps answering long after it should have asked for help. It answers wrong, on a route nobody sized for, and the first person to notice is a customer.

That is the failure an investor is probing for in diligence. Not which model you picked, but whether anyone can show what the system did when more arrived at once than it could serve, and how much room was left above the line when it happened.

Speed, leverage and risk are the three numbers we are judged on.

Every engagement reports against the same three, from a seed-stage voice product to a Series C platform fitting agents into a core system.

Speed

Weeks to live traffic rather than quarters, because the capacity work happens in the first fortnight instead of the last.

Leverage

Engineers who have carried production systems before, so none of the learning curve gets billed to you.

Risk

Guardrails, evaluation and hallucination control designed in at the start, where they cost the least to hold.

Three competencies, one team that carries the load.

Artificial Intelligence

Architecture, guardrails and evaluation designed together, so reliability is a property of the system rather than a repair made under pressure.

Blockchain Innovation

Decentralised applications sized for volume, on secure and transparent ledgers that keep data intact as it moves across enterprise ecosystems. Supply chain transparency. Tokenisation.

Machine Learning

Forecasting through to hyper-personalisation, so an archive that only ever cost you storage starts carrying weight. Predictive analytics. Computer vision.

Four steps, and the headroom gets sized in the first one.

The same route whatever the stage, because the question is always how much arrives at once and what happens to the rest.

  1. 01

    Discover

    Product, data and every decision the agent will own get written down inside the first week.

    You leave with a scoped first release and a figure for what it has to absorb on day one.

  2. 02

    Prototype

    Something operable reaches your team quickly, so judgement forms against behaviour.

    It runs against the volume you expect, not against a single tidy request typed by the person who built it.

  3. 03

    Launch

    The release goes out hardened, with guardrails enforced and the audit trail already writing.

    Concurrency limits, retries and the shed path are all settled before a customer touches it.

  4. 04

    Iterate

    Logged interactions feed the next revision, and tuning continues as the product moves.

    Headroom gets re-sized each time volume climbs, which is how the fortieth week stays as quiet as the first.

Nothing held. Four detail lines released.

Four agents carrying real customers right now.

  • 01

    Propizone CRM Voice AI

    A portal enquiry at eleven at night used to arrive at voicemail and wait until morning. The voice layer answers in eight seconds and qualifies the lead while the person is still reading the listing.

  • 02

    CandiPro ATS Voice AI

    Five hundred applicants once meant five hundred screening calls queued behind one recruiter. The agent now takes the hiring manager's interview itself and returns the shortlist in rank order.

  • 03

    Neo-Bank Voice AI

    Inside a US neo-bank app, a voice layer takes account questions and then moves the money, with a confirmation step on every transfer before it clears.

  • 04

    ReachOut Voice AI

    ReachOut's agents call back within seconds of the form landing, so the conversation happens while the intent is still warm rather than three days later.

One agreement, sized once, held across every company you back.

Rates, priority access and delivery frameworks get settled at the fund level and then hold everywhere you have money in. We learn the thesis alongside your partners, so a founder skips the vendor search and arrives at a first call already briefed.

Auditors name eight frameworks. The architecture already meets them.

Data residency, PII handling, audit trails and explainability are fixed in the design, so a review meets a system that already complies instead of a hardening sprint booked for the week before.

What a fund gets when the headroom is bought early.

Tell us what the first real hour looks like.

Describe the agent, the system it has to live inside, and roughly how much arrives at once. An engineer comes back with an approach, an effort range, and the first limit worth setting.