ventuno --describe

Realistic, executable worlds where agents do real work.

Ventuno builds fully synthetic software environments — working applications, realistic data, long-horizon tasks and outcome-based verifiers — for evaluating, training and improving AI agents.

talk to us watch FAST TV live →

// the problem

Agents need somewhere to learn real work.

Agents do well on isolated, well-defined problems. Real work involves incomplete information, interconnected systems, legacy decisions, persistent data and changes whose effects surface elsewhere.Static benchmarks capture only part of that. Production systems are too sensitive to use as training grounds. Synthetic worlds are the controlled alternative: realistic systems where agents can attempt work safely, get reliable feedback and improve through repetition.

// a world has four layers

working software

Frontends, services, APIs, databases, queues, caches — a complete ecosystem.

synthetic data

Organizations, users, transactions and operational history. No customer data, no PII.

reproducible exec

Containerized, isolated, resettable — repeatable across models and harnesses.

tasks + verifiers

Controlled starting states, public feedback, hidden outcome-based evaluation.

Together they create environments where an agent does the work — not merely answers questions about it.

// our first world

FAST World

A synthetic, multi-service software platform built from the ground up on a modern stack. FAST evaluates and trains coding agents on realistic engineering work: defect resolution, feature development, refactoring, migrations, performance and security — inside a persistent ecosystem with interacting services and real system state.

Every task starts from a controlled state and ends with a verifier the agent cannot read. Verifiers examine outcomes rather than diffs: whether system state is correct, whether behaviour elsewhere still holds, whether performance and security survived, and whether the result was achieved legitimately rather than by disabling a check.

Results come back as success rates by task family and horizon, the failure modes behind them, and full trajectories you can inspect step by step.

watch FAST TV live →request a FAST evaluation

Five linear channels, scheduled and streamed by the same infrastructure agents operate inside FAST World. Watch the television — then picture the agent running everything behind it.

[ read the FAST World primer ]

task_family

horizon

defect_resolution

short

cross_service_change

long

database_migration

long

legacy_refactor

long

incident_investigation

medium

ambiguous_requirements

medium

// how labs work with us

evaluate

Run a confidential task pack against a reproducible world. Baselines, success rates by family, failure analysis, trajectory inspection. Useful when you need to know where an agent breaks down on long-horizon work before committing to a training run.

train

Licence a world and its tasksets: parameterized families, reproducible starting states, outcome rewards, train and held-out splits. Tasks generate from families rather than being hand-written, so volume scales without collapsing into memorisable cases.

build with us

Bring a domain or a known model weakness. We provide world architecture, synthetic data, task design and verification. Worlds beyond software engineering — enterprise workflows — are in development on the same foundation.

Worlds run as local Docker, in containerized eval frameworks, on hosted platforms, or inside your own infrastructure — independent of any single training stack.

// why ventuno

Ventuno has spent more than two decades building and operating complex software systems — from testing infrastructure for Sonoa Systems, which became Apigee, to a video distribution platform serving more than 300 publishers, and later a multi-platform streaming SaaS product. We are now applying that systems experience to building realistic synthetic worlds for AI agents.

[ our journey ]

20 yrs

systems in production

300+

publishers served

full platform rebuilds

top 10

comscore india, 5 yrs

Build agents that can handle the real thing.

Working with foundation-model labs, coding-agent companies, computer-use teams and post-training researchers.

discuss a world FAST eval