Voice, speech, vision and private AI

AI Solutions

Production AI built into your product and operations — voice agents, speech and audio, document and image understanding, private models and integrations with the AI tools your team already uses.

What we do

What’s included

Technology

Tools we work with

Why Bitfumes

Built by engineers who ship

  • Senior team, no hand-offs

    The engineers on your first call are the ones who build your product.

  • 10+ years of engineering leadership

    Led by Sarthak Shrivastava, Docker Captain, AWS Certified Solutions Architect, AWS Certified Developer.

  • We teach this for a living

    156K+ developers learn from our founder on YouTube, and 100K+ on Udemy.

  • Production, not prototypes

    Tests, monitoring and handover are part of every build, not extras.

100+
Projects delivered
40M+
Users reached
98%
Client retention
9 yrs
In business

How to start

From first conversation to production

  1. 1

    Talk to us

    Tell us the problem. We come back with a straight view on whether it is worth building.

    Get in touch
  2. 2

    Build

    A senior team embeds with yours and ships in short cycles, with a demo every week.

  3. 3

    Run and improve

    We hand over cleanly, or stay on to monitor, support and extend what we built.

FAQs

Common questions

What is a voice AI agent?

Software that holds a spoken phone conversation using speech recognition, a language model and a synthetic voice, so it can answer questions and take actions during the call.

Can callers tell they are talking to AI?

Modern voices sound natural, but we recommend the agent says it is an AI assistant, and many regions require disclosure.

Which languages do you support?

English and the major Indian languages, including mixed speech such as Hinglish, plus other languages depending on the model chosen.

Can it run offline?

Yes. Some speech models can run on the device itself, with no internet connection and no audio leaving the machine.

Are private models as good as the big cloud models?

For many focused tasks, such as transcription, classification and extraction, open models are close enough. For open-ended reasoning, cloud models often still lead, and we will tell you where that trade-off falls for you.

What hardware do we need?

It depends on the model. Some run on a laptop; larger ones need a GPU server. We size this during evaluation.

What is MCP?

The Model Context Protocol is an open standard for connecting AI assistants to external tools and data, so one connector can work across several AI apps.

Is it safe to connect AI to our systems?

It can be, with the right design: least-privilege access, per-user permissions, logging and human approval for actions that change data.

Is this the same as OCR?

OCR turns an image into text. Document AI goes further: it understands the layout and meaning, so it can find the total on any invoice, not just one template.

Can it handle handwriting and photos?

Often, yes, depending on quality. We test on your real samples before committing.

Insights

Related reading

Next step

Want this built into your business, not just explained?

Tell us the problem and we'll come back within one business day with a straight view on whether AI is worth it for you, and what it would take to build.

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