---
title: "Generative AI Agency | From Prototype to Real Users"
description: "A generative AI agency for the gap between a working prototype and a feature real users trust: retrieval quality, evaluation, streaming interfaces, and cost that scales."
image: "https://foundrysoft.co/api/og?type=page&title=Generative+AI+Agency+%7C+From+Prototype+to+Real+Users&st=A+generative+AI+agency+for+the+gap+between+a+working+prototype+and+a+feature+real+users+trust%3A+retrieval+quality%2C+evaluation%2C+streaming+int%E2%80%A6"
url: "https://foundrysoft.co/services/generative-ai-agency"
---

Generative AI agency · Built in India for US companies

# A generative AI agency for teams shipping to real users

We are a generative AI agency that mostly gets called when the prototype works and the launch does not. The gap is usually retrieval quality, unhandled input variety, and no way to tell whether a change helped.

Book a 30-min scoping call [See our work](https://foundrysoft.co/work)

No sales script. You talk to the engineers who'd build it.

9+ hrs

Timezone overlap

Our team works a shifted day so you get real-time standups and same-day turnarounds in your time zone, not next-morning replies.

100%

You own the IP

Every line of code, model weight, and prompt is yours from day one. NDAs and clean IP assignment are standard, not an upsell.

Senior

No juniors hidden on the bill

You work directly with the engineers building your system. No account managers sitting between you and the people writing code.

Weeks

To first deployment

We move from scoping to a working system in production in weeks. Most engagements ship something usable inside the first month.

## What we build

Concrete systems we ship, tuned to your data and your stack.

### Prototype to production

The unglamorous work between a demo and a feature: edge cases, error handling, permissions, and latency people will tolerate.

### Retrieval quality

Chunking, hybrid search, and reranking. Most failing systems have a retrieval problem being treated as a model problem.

### Streaming interfaces

Chat and generation UIs that feel fast, handle partial failure, and do not lose the user's work when a request drops.

### Evaluation before launch

A scored test suite from real cases, so the go-live decision is a number rather than a feeling.

## How we work

01

### Scope & evals

We pin down what success means and build the evaluation set before writing the feature, so quality is measured, not guessed.

02

### Build in the open

Weekly demos against real data. You see progress every week and can change direction before it gets expensive.

03

### Ship & instrument

We deploy with logging, cost tracking, and guardrails in place, then tune against production traffic.

04

### Hand off or stay

Take the keys with full docs, or keep us on for iteration. Either way you're never locked in.

## Questions, answered

### Our demo impressed everyone and the launch went badly. Why?

+

The demo ran on inputs someone chose. Production runs on inputs nobody chose. Build against a random sample of real data from week one and your day-one number is embarrassing, which is exactly why it is useful.

### Do you do creative and content generation work?

+

We build the systems behind it: generation pipelines, brand and policy constraints, review workflows, and the marking of generated content that transparency rules now require.

### How do you measure quality on something subjective?

+

Pairwise comparison against a reference set, plus hard checks for the things that are objective, like citations resolving and constraints being respected. Perfect measurement is not available, but better than nothing beats arguing.

### What is the fastest path to something live?

+

A narrow feature for one user group, in production, in weeks. Narrow things generate real numbers and real numbers fund the next phase.

## Let's scope your build.

Tell us what you're trying to ship. We'll tell you honestly whether AI is the right tool and what it would take.

Start the conversation

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