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's inside
5 servicesWhat we do
What’s included
Voice AI agents
AI that answers and makes calls for you
Learn moreSpeech & audio AI
Transcription, captions and voice in many languages
Learn morePrivate AI
Models that run on-device or in your own cloud
Learn moreAI integrations (MCP)
Connect Claude and ChatGPT to your own tools
Learn moreDocument & vision AI
Pull data from invoices, forms and images
Learn more
Technology
Tools we work with
- Speech-to-text
- Text-to-speech
- ElevenLabs
- LLMs
- Telephony APIs
- CRM & calendar integrations
- Sarvam AI
- Whisper
- FFmpeg
- Python
- TypeScript
- Open-source LLMs
- Ollama
- Docker
- GPU servers
- AWS
- Model Context Protocol
- Claude
- ChatGPT
- Claude Skills
- Vision LLMs
- OCR
- Flutter
- Firebase
- Cloud Functions
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.
How to start
From first conversation to production
- 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
Build
A senior team embeds with yours and ships in short cycles, with a demo every week.
- 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
- EngineeringAgentic AI: what actually changes when a model can take actions.Chat is a conversation. Agents are a system that reads, decides, and acts — which means the engineering bar, and the failure modes, are completely different.Read
- AI StrategyChoosing an LLM for production isn't a benchmark exercise.Leaderboards tell you which model is smartest in a vacuum. Shipping software tells you which model is cheapest, fastest, and most consistent for your exact task — a different question entirely.Read
- EngineeringMCP: stop building the same AI integration five times.Every AI assistant your team adds needs the same connection to your order database, your CRM, your ticket queue — built again, in a different SDK. Model Context Protocol lets you build that connection once.Read
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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