AI · APPLICATIONS · INFRASTRUCTURE

Better systems.
AI where it
earns its place.

Reduce IT waste with sound engineering, open-source software and intelligent automation. We know where AI helps—and where a better integration, clear rules or a faster database is the right answer.

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Complex systems. Experienced engineers. See the work
IT consulting and engineering since 2021
THE ENGINEERING BETWEEN THE LAYERS
APPLICATIONSCONNECTED DATARELIABLE FOUNDATIONS

Make applications, data and infrastructure work together.

JUDGMENT BEFORE TECHNOLOGY

Does this actually
need AI?

Fix the bottleneck first. Choose AI, conventional software or a combination around the work—not the trend.

APPLICATIONSCONNECTED DATARELIABLE FOUNDATIONS
01 / THE RIGHT TOOL FOR THE WORK

Exact calculations, access enforcement and repeatable data movement.

A slow database may need indexing. Disconnected software may need an API. Neither automatically needs AI.

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YOUR NEXT CHAPTER

Where do you want
to go from here?

You bring the context.
We bring the engineering to move it forward.

01 / BUILD

I’m building
a product.

Add experienced developers, build an application, or get your AI-built app ready for production.

Engineering for startups02 / CONNECT

My systems need
to work together.

Connect applications, modernize older software and introduce AI into everyday workflows.

Engineering for businesses03 / OPERATE

I need a stronger
technical foundation.

Get specialist support for cloud infrastructure, servers, databases and production operations.

Infrastructure & operations
TWO WAYS TO PUT AI TO WORK

A second brain.
AI output worth using.

AI SDRs, BDMs & GTM

ANSWER REVIEWEvidence before confidence.[1]?Source linked / Missing evidence flaggedExplore AI Sales & GTM

Your business, with a second brain

Reuse company knowledge. Reduce token waste. Get answers your team can check and use.

SHARED CONTEXTSources · access · freshnessAnswers with evidenceBuild your AI second brain

Illustrative workflows. Responsibilities and integrations are defined for each project.

ILLUSTRATIVE WORKFLOW EXAMPLES

A prompt starts it.
Engineering makes it useful.

Explore the data, checks and handoffs behind an AI request. These examples explain a design approach; they are not live AI outputs or client results.

EXAMPLE REQUEST

Find the policy, show the evidence.

Using the current approved policy, list our vendor onboarding steps in no more than 6 bullets. Cite each source. Flag missing or conflicting information; do not invent steps.
  1. 1
    Check access

    Use only sources the requesting user can access.

  2. 2
    Retrieve evidence

    Retrieve relevant policy sections, not the full document archive.

  3. 3
    Construct an answer

    Check the requested format and source support before returning the answer.

Response structureProcess steps + source references + any missing information

If sources conflict, surface the conflict for review.

PRACTICAL PROBLEMS. ENGINEERING OPTIONS.

Less spend.
Less work between systems.

Explore common challenges for growing and mid-sized businesses. These are illustrative solution scenarios, separate from our delivered client case studies.

ILLUSTRATIVE SCENARIO · SaaS cost cutting

Too many subscriptions. Too little value.

Reduce unused seats, overlapping subscriptions and unnecessary upgrades without breaking the workflows people rely on.

Explore the approachILLUSTRATIVE SCENARIO · Cloud cost reduction

A cloud bill that keeps growing. A workload that does not.

Find idle resources, oversized databases and expensive data movement while protecting performance, recovery and availability.

Explore the approachILLUSTRATIVE SCENARIO · Reporting & reconciliation

The weekly report takes a day to assemble.

Connect operational data and reconcile exceptions so people can review the business instead of rebuilding spreadsheets.

Explore the approachILLUSTRATIVE SCENARIO · Identity & workflow automation

Every new hire starts another chain of access requests.

Coordinate employee onboarding and offboarding across applications, approvals and software licenses.

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ENGINEERING CASE STUDIES

The work between
a prototype and production.

AI capabilities, complex integrations and high-volume systems. See the engineering problems behind selected engagements.

AI & real-time applications

Bringing real-time interviews and multiple AI capabilities into one platform.

An interview integrity platform combining deepfake detection, speech analysis, gaze tracking, an adaptive question engine and generative AI.

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Agentic AI / in-house applications

Bringing agentic AI into applications a business already depends on.

Agentic AI added across the corporate travel company’s systems by the team responsible for building and operating them.

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Corporate travel

Making travel applications, payments and predictive data work together.

Complete development, infrastructure, GDS, payments and analytical data systems—built, managed and supported as the corporate travel company’s core provider.

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High-volume transactions

Untangling a message bus supporting high-volume transactions.

Message-bus architecture and cleanup work for high-volume transactions at the retail business.

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Explore all case studies
DEEP EXPERTISE.
ACROSS YOUR STACK.AzureAWSGoogle CloudKubernetesSQL ServerPostgreSQL
LET’S GET TO WORK

Where is technology costing you too much?

Software spend. Repetitive work. Disconnected systems. Let’s find the engineering changes that make a difference.

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PAST CLIENTS

Experience across demanding businesses.

BTP Automation
Cru
Costco
Publix
Texas Health and Human Services
Werner Enterprises
Corteva
Community Health Choice Inc.
Capifiq

Selected organizations from our broader client experience.