Service 01

AI automation that takes the busywork off your team.

Workflow automation, LLM assistants and document AI built into the tools you already run, measured against your own data and kept working in production.

Practical AI, built in From First workflow to production Four ways to work with us
  1. 01 AI Automation You’re here
  2. 02 Team Augmentation
  3. 03 Software Development
  4. 04 MVP Development
Is this for you?

Losing hours every week to repetitive work, copy-pasting or answering the same questions?

We find the workflows worth automating, build the automation or assistant around your systems and data, and test it on real cases before your team relies on it.

Automation your team can trust.

What’s included

From the first workflow to production.

Everything it takes to move a manual process into automation that holds up.

  1. 01

    Workflow review: what to automate, and what to leave alone

  2. 02

    Automations and agents connected to your existing tools

  3. 03

    LLM assistants grounded in your own documents and data

  4. 04

    Document processing: extraction, classification and routing

  5. 05

    Testing on real cases before launch, monitoring after

What we automate

Automation where it pays back fastest.

Pick a kind of work and watch it run, connected to the tools you already use.

Workflow · New order to CRM Running
  1. Trigger · Inbox Order email arrives
  2. AI step Read and extract
  3. Action · CRM Create the record
  4. Action · Chat Tell the team
Activity Order email received Customer, items and total extracted Record created in your CRM Sales channel notified
Every automation is tested on real cases before launch, and monitored after. Automate a workflow
How it works

A proven process for every automation.

  1. 01

    Share your goals

    Tell us what you’re building and where you’re stuck.

  2. 02

    Get a clear plan

    We suggest the engagement model, timeline and team.

  3. 03

    Build in the open

    Agile sprints with direct, transparent communication.

  4. 04

    Launch

    Quality tested and deployed to production.

  5. 05

    Support and scale

    30 days of complimentary maintenance, then SLA plans.

How we bill, and what happens after you get in touch
Client voice
They listen to you. They make sure your ideas are heard and then they implement them very timely.
Nasrin Nawa Senior Communications Specialist, Afghan Future Fund
Technology

The stack behind our automation work.

From the first workflow to automation in production, these are the tools we reach for most.

Models and LLMs 5
OpenAI Claude Llama Mistral Hugging Face
Machine learning 4
PyTorch TensorFlow scikit-learn XGBoost
Data pipelines 5
Python Pandas Apache Spark Airflow dbt
Search and retrieval 4
pgvector Pinecone Elasticsearch LangChain
MLOps and cloud 4
AWS SageMaker Azure ML MLflow Docker
Integration 4
FastAPI REST and GraphQL Webhooks Zapier
Already have a stack? We build with the tools your team uses today. Talk to an engineer
FAQ

Questions, answered.

How we handle your code and data
Which work is worth automating?

Work that is frequent, rule-heavy and already written down somewhere: triaging requests, moving data between systems, reading documents and answering the same questions. We start with a short review of your workflows and tell you which ones will pay back, and which are better left to people or plain code.

Will it work with the tools we already use?

Yes. We connect to the systems you already run, such as Microsoft 365, Google Workspace, your CRM, ERP or databases, through their APIs. You do not need to replace anything to get started.

How do you stop an AI assistant from making things up?

Assistants answer from your own documents and data, cite where each answer came from, and say so when they do not know. Before launch we test them on real questions from your team and only ship once the results hold up.

Who can see our data?

Only the people working on your project, under an NDA. We use model providers whose business terms exclude your data from training, and we can run on your own cloud account when your policies require it.

What does it cost to run once it is live?

It depends on volume and the models used. We estimate running costs during discovery, choose the smallest model that does the job well, and monitor usage after launch so there are no surprises.

Ready when you are

Have a process to automate? Let’s explore it.

Share your requirements and we will propose a plan, timeline and team structure that fits.

Prefer to talk? Book a free 20-minute call

Working worldwide Say hello hello@axceera.com
Johannes Lang Gajan Srikanthan Janaka Weerabaddana Dissanayake Aminda Keerthiratne
Join teams at Ventures Beyond Borders, Aethenos and IML.