AI Consultancy & Strategy
Workflow automation
We build AI agents and automations that take repetitive, multi-step work off your team: reading emails and documents, updating systems, drafting replies and routing exceptions to a person. They run on the tools you already use, with no migration.
AI agent at work
RunningIs this for you?
You’ll get value from this if…
- People copy data between systems by hand every day
- Inboxes and queues fill with requests that follow the same pattern
- Work stalls waiting for someone to triage, approve or file it
- Earlier rule-based automation broke whenever the input changed
Benefits
What changes for your business
Time back for your team
Repetitive steps move to software, so people handle the judgement calls.
Fewer manual errors
Data is read and entered the same way every time.
Work that doesn't wait
Requests are picked up as they arrive, not when someone gets to the queue.
What you get
What we deliver
Agent or automation
The workflow built end to end, connected to your email, CRM, ERP or other systems.
Human-in-the-loop checks
Clear points where a person reviews or approves before anything important happens.
Run log and alerts
Every run recorded, with alerts when something needs attention.
Runbook
How it works, how to change it, and what to do when it flags an exception.
How it works
From first call to running in production
- 01
Shadow
We watch the current process and collect real examples, including the messy ones.
- 02
Design
Decide what the agent handles, what it escalates and where people approve.
- 03
Build and test
Build against real examples and measure it before it touches live work.
- 04
Go live
Start supervised, then widen what it handles as confidence grows.
Example applications
What this looks like in practice
Typical applications of this service. Illustrative, not client case studies.
- 01Reading invoices and entering them into your accounting system
- 02Triaging inbound email and routing it to the right team
- 03Updating CRM records from calls, forms and messages
- 04Pulling reports from portals that have no API
Technology
Tools we work with
- AI agents
- Model Context Protocol (MCP)
- APIs & webhooks
- Browser automation
- Python
- TypeScript
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 an AI agent?
Software that uses a language model to decide and carry out the steps of a task, such as reading a request, looking something up and updating a system, rather than following a fixed script.
Do we need to replace our current systems?
No. We connect to the systems you already run through their APIs or, where there is none, through the interfaces people use today.
What happens when the agent is unsure?
It routes the case to a person with the context it gathered, instead of guessing.
Is this the same as RPA?
It overlaps. Traditional RPA follows fixed rules and breaks when inputs change. AI agents can read unstructured inputs like emails and documents and decide the next step, with people approving where it matters.
How do we know it is working?
Every run is logged, exceptions are surfaced to a person, and we agree up front how success is measured.
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
- 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
- AI StrategyClaude in Chrome: automate the login no API will ever cover.Some systems will never get an API — the supplier portal, the benefits site, the government form. Claude in Chrome watches you do the task once and does it again itself, from inside your own logged-in browser.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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