AI Systems & Agents

AI agents that do real work, on your real data.

Most AI looks great in the demo and does nothing useful in production. We build the agents and systems that resolve tickets, answer from your own knowledge and run the busywork, grounded in data you can trust.

RAG on your data · tools & guardrails · evals · human-in-the-loop · monitoring.

SOC 2 Type II · ISO 27001 · GDPR · You own the code

Inside an agent
Your datadocs · CRM · tickets
Agentgrounded · guardrails
Resolves it
To a human
PythonPythonReactReactNext.jsNext.jsNode.jsNode.jsAWSAWSGCPGCPAzureAzureDockerDockerKubernetesKubernetesPostgreSQLPostgreSQLMongoDBMongoDBSnowflakeSnowflakeRedisRedisStripeStripe
01The problem

You've felt this.

“Our AI demo wowed everyone, then did nothing useful in production.”

“It answers, but we can't trust it on the cases that matter.”

“We bolted a chatbot on and customers ignored it.”

“Every vendor sells 'AI'. None of it runs on our data.”

02Why demos stall

Why a clever demo won't ship.

1 clean case

a demo runs on one clean case; your business sends ten thousand messy ones.

Trust = use

an agent your team can't trust is an agent nobody opens.

80%+

of AI projects never reach production (RAND) because the data and the measurement were missing.

03Method

How we ship agents that get used.

  1. 01

    Ground it in your data.

    RAG over your docs, CRM and tickets, so answers come from your business, not a generic model.

  2. 02

    Give it tools and guardrails.

    The agent can act, inside limits you set, with the risky steps gated.

  3. 03

    Measure it.

    Evals against real cases, so you know it actually resolves, not just responds.

  4. 04

    Human-in-the-loop.

    The genuinely hard calls go to a person with full context.

  5. 05

    Monitor and improve.

    We watch quality as your data and the models change.

04What we build

What we build.

01

Support agents

resolve tickets, not just reply.

02

Knowledge answer-engine

ask anything over your own docs.

03

Workflow automation

the busywork between your apps.

04

Back-office ops

reporting, follow-ups, reconciliation.

05

AI in your product

search, summaries, a copilot.

06

Regulated advisor bots

guidance with citations and an audit trail.

07

Content systems

draft, repurpose, schedule.

08

Fractional AI partner

find the highest-ROI wins and build them.

05Our unfair advantage

Most AI projects fail on data, not models.

We spent years building the hard part, reliable pipelines that pull, clean and structure your data. That is what our agents run on, so you get a system that knows your business.

06Engagements

Start with a plan and a number.

07How we work
  1. 01 · Call

    Thirty minutes on the actual problem

    Free
  2. 02 · Scope

    A written plan, fixed price

    1-2 weeks
  3. 03 · Pilot

    Working software on your real data

    3-6 weeks
  4. 04 · Run

    We keep it standing, or hand it over

    Ongoing

SOC 2 Type II · ISO 27001 · GDPR · On-prem on request · You own the code and data

08FAQ

Straight answers.

“Won't the base models just get better?”
They improve, but the durable asset is your grounded data and evals; that keeps paying off across upgrades.
“Is our data safe?”
Sandboxed, read-only where possible, SOC 2-aligned, on-prem on request. You own everything.
“Can it plug into our stack?”
Yes, we build around your existing tools and data.
“What if AI isn't the answer?”
Then we tell you. We would rather say no than sell you a science project.
09Final step

Tell us what your team does by hand. We'll tell you honestly if AI can do it.

Free 30-minute call, no pitch deck. We'll tell you honestly whether it's worth automating, and roughly what it costs.

Reply time
Same working day
Team
In-house, full-time
Clients in
Asia-Pacific · Europe · Americas