Cluebyte Start a project

AI agents that do
the work and show
their reasoning

Agents that plan multi-step tasks, call your systems through safe, narrow tools and write down why they did what they did. A person approves anything that matters.

Talk about an agent What one costs to run
Typical timeline
8–14 weeks to the first agent in production
Team
1 AI engineer, 1 back-end engineer, 1 QA engineer, part-time lead
You provide
A process owner for 2 hours a week and API access to your systems

What we build

A process,
not a chatbot

Every agent we ship has the same 4 parts. That's what makes it safe to give it real work.

A written plan

The agent breaks a request into steps and records them before it acts, so you can see its intent.

Narrow tools

It can only call the actions we give it, such as "book slot" or "draft reply", each with its own limits.

Human checkpoints

Anything above a threshold you set, such as cost, risk or low confidence, waits for a person.

A decision log

Every input, tool call and output is stored, searchable and exportable for audit.

Where agents earn their keep

Good first jobs
for an agent

High-volume, rules-heavy work that is currently done by copying between 2 or more systems.

  1. 01
    Inbound triage

    Read emails, forms and attachments, classify them, pull out the key fields and route each one.

  2. 02
    Scheduling and booking

    Match requests to availability across calendars and resources, propose slots and confirm them.

  3. 03
    Order and claims handling

    Check a request against policy, gather missing information and prepare the decision for approval.

  4. 04
    Research and reporting

    Gather weekly figures from internal systems, write the summary and flag anything unusual.

Stack

The model per task,
not per vendor

We test 2–3 models against your real cases and choose on accuracy, latency and cost. Swapping later is a configuration change.

Models
ClaudeGPTGeminiLlamaMistral
Orchestration
PythonTypeScriptMCPLangGraphTemporal
Data and retrieval
PostgreSQLpgvectorElasticsearchS3
Evaluation and monitoring
Evaluation suitesOpenTelemetryGrafana

Questions

What clients ask
before they start

Will the agent make mistakes?
Yes, sometimes, and so do people. We measure the error rate against your real cases before launch, set confidence thresholds so uncertain cases go to a person, and review the log weekly for the first 3 months.
Where does our data go?
We use model providers' business tiers, which don't train on your data, and can deploy in your own cloud account and region. Personal data can be masked before it reaches a model.
How much does it cost to run?
Model usage is usually the smallest cost. Hosting, monitoring and the people who review edge cases matter more. We give you a 12-month running-cost estimate with the proposal. Read our cost breakdown.
Can we start small?
Yes. Most clients start with a 3-week proof of concept on one task, using their own historical data, and decide on a full build once they've seen the results.
Who owns the agent?
You do. Code, prompts, evaluation sets and infrastructure sit in your accounts from the first commit.

Start with one task

Bring us
a process.

We'll tell you if an agent should run it. A 30-minute call, then a written opinion within a week. No charge.

Book a call