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AI-native engineering, from first spec to production.

Applivity builds. Senior, outcome-owning teams design, ship and integrate software the AI-native way - AI in the loop at every stage, qualified engineers accountable for every output, delivered on infrastructure your security team governs.

The shift

Not another dev shop. An AI-native one.

AI-native engineering is an operating model, not a plugin. AI agents are part of the team, so the bottleneck moves from typing code to reviewing, integrating and governing it. That is where our senior engineers spend their judgement - and where a small, well-run team now outpaces a large one.

AI accelerates requirements, code, tests and documentation
Verification gates and human review before anything ships
Fewer handoffs, faster cycles, predictable cost
AI-native engineering
Engineering team working with AI-assisted tooling
What you can engage us for

Six ways we build with you.

AI Engineering Pods

A senior, cross-functional team that owns a product outcome end to end - architecture to production, one accountable owner, weekly demos.

Explore pods

Product, POC & MVP builds

Turn a use case into a running app in weeks. Prove value on real data before you commit to a full build.

See the fast-track

Custom enterprise systems

Line-of-business platforms, portals and workflow systems built to the standard our regulated work demands.

Integration & legacy modernization

Wire AI and new apps into SAP, Oracle and the HSE, CMMS and BI systems you already run - the phase most projects underestimate.

QA, DevOps & platform

Automated testing, CI/CD, observability and cloud or on-prem delivery - your tenant, your governance, your uptime.

Immersive & AR/VR

Training and visualization on Meta Quest and assisted-reality devices, from our AR/VR lab.

Visit the lab
Applied AI
Computer vision analysing an industrial field scene
Under the hood

The AI capabilities we bring.

Not slideware. These are the working parts we build into your systems, chosen for the job rather than the hype.

Computer vision for inspection, defect and PPE detection
Voice and multilingual NLP for hands-free field capture
LLM document, report and SOP automation - with review
Retrieval and search across your own documents
Data pipelines, MLOps and field model management
Enterprise integration into the systems of record you run
Engagement models

Own it, embed, or hand it over.

Three ways to work together - pick the operating model that gives you the fastest safe path to production. Whichever you choose, you own what we build: capability, not dependency.

We run it

A managed pod owns delivery inside your approved boundary. You get outcomes, weekly demos and one point of accountability, not a stack of timesheets.

We embed

Senior AI-native engineers join your team and lift its delivery - bringing our workflows, review gates and tooling with them.

We build and hand over

We stand up a POC, MVP or platform, document it and hand you a system your own team can run and extend.

How we deliver

One AI-native path, spec to production.

1

Discover & shape

We map the workflow, the risk and the win before a line is written - so scope is honest and the business case is clear.

2

Spec-driven design

A precise specification steers both engineers and AI agents, cutting rework and keeping everyone aligned on the same target.

3

Build with AI in the loop

AI accelerates code, tests and docs while senior engineers direct the work and own the decisions.

4

Review gates

Nothing progresses without human review - security, quality and correctness checked against clear thresholds.

5

Integrate

We wire the system into your identity, data and systems of record - the phase that decides whether AI ever reaches production.

6

Operate & hand over

Weekly demos, monitoring and documentation, so your team can own and extend what we built.

Security & governance

Built for the people who sign off.

Security, legal and data-privacy reviewers weigh governance as heavily as features. We build so those reviews are short.

Runs inside your approved boundary - your cloud tenant, our managed cloud, or on-premises
Your identity, SSO and Active Directory - your retention and residency policies
NDA-first, with data minimization by design
Human review on every AI-generated output
Your IP is yours - clear ownership and handover
See enterprise deployment
Governed by your rules
Secured enterprise infrastructure
Proven where it counts

Two decades of consequential systems.

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Verified client rating on Clutch
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Years of regulated enterprise delivery
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Applications processed, US government platforms
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National energy operators running our AI
Questions

What buyers ask first.

How is an AI Engineering Pod different from staff augmentation?

The pod owns the outcome - scope, technical path, release and handover - not just seats on a call. You get one accountable team, weekly demos and measurable results, instead of managing individual contractors.

What does “AI-native” actually change?

AI accelerates every stage - requirements, code, tests, documentation - so a small senior team delivers more, faster. The work shifts from typing to review and judgement, and qualified engineers own and check every output before it reaches you.

Do you only build industrial AI?

No. Industrial and field AI is our focus, but the same teams build enterprise platforms, portals, integrations and line-of-business systems. The discipline is the same wherever accuracy matters.

Where do our code and data live?

On infrastructure you approve - your cloud tenant, Applivity-managed cloud, or on-premises - governed by your identity, SSO and retention policies. We work NDA-first and design for data minimization.

Who owns the IP?

You do. Work produced for you is yours, with clear ownership and documentation handed over so your team can keep moving.

How quickly can we start?

A scoped POC or MVP can be running in weeks. Most engagements begin with a short discovery to map the workflow and the win before a line is written.

Next step

Put a pod on your problem.

Tell us the workflow. We will map the win and the approach before a line is written.