Time-to-production
Median time from contract signature to a live system, across AI-enabled engagements between 2023 and 2025.
NEXUS11 weeks
Industry26 weeks (industry median)
AI-powered software,
shipped in weeks.
We build production AI systems, web platforms, and automations for organisations that need them live, not in a slide deck. We also help engineering teams adopt AI-augmented development, so they ship faster with the team they already have.
Currently accepting new briefs.
Engagement arc~12 wk to production
- BriefDay 0
- DiscoverWk 2
- BuildWk 6
- Hand overWk 12
Discovery 2 wk
Build 8–10 wk
Handover 1–2 wk
Accepting new briefs
Currently shipping in three sectors:
reproductive health, care and compliance, and mid-market SaaS.
Reply
≤ 1 business day
First step
Brief, then call
10K+
Patients served
150+
Facilities deployed
40%
Admin time recovered
98%
On-time delivery
02What we build
A small studio. A full delivery stack.
Seven disciplines, one team. Every engagement is led by a senior engineer who stays on the project from the first call to the final handover. We choose the right tools for the job and adapt to your team's existing stack.
- 014–10 weeks
Applied AI engineering
Chatbots, copilots, document assistants, and retrieval systems that actually work in production. Built with the major model providers, monitored end to end, and designed so your team can run them after we leave.
- 026–12 weeks
Product engineering
Customer-facing web platforms, internal tools, dashboards, and mobile apps. Built to ship on time and to scale once they do.
- 033–6 weeks
Data and integrations
Connecting the systems you already have (CRMs, EMRs, spreadsheets, third-party APIs) into clean pipelines, reporting layers, and dashboards your team can trust.
- 042–4 weeks
Infrastructure and DevOps
Production hosting, deployment pipelines, monitoring, and on-call playbooks. Set up properly the first time, with cost controls so the cloud bill does not surprise you.
- 05Ongoing
Compliance and assurance
HIPAA, GDPR, and SOC 2: designed in from day one, not retrofitted before an audit. Control mapping, evidence collection, and audit-ready documentation included.
- 066–12 weeks
AI engineering transformation
For engineering teams of 8–80 people. We roll out AI-augmented development (Cursor, Claude Code, Copilot, AI-assisted testing) the right way, so you ship faster without rewriting the team or the codebase.
- 07Monthly
Embedded technical advisory
Fractional CTO support, architecture reviews, and hiring panels for teams between founder-led and a full engineering org.
Tools are chosen per engagement. We work across the major model providers, cloud platforms, and open-source ecosystems, and recommend the right combination once we understand your scope and team.
03How we work
One team. Three phases. No handoffs.
We do not separate strategy from engineering. The same senior team that writes the brief also ships the code, runs the deployment, and trains your team to take it over.
Phase 01
Discover
Two weeks with your team. We map how the work happens today, find where software (and AI, where it fits) moves a real number, and produce a written brief your team and ours can both build from.
Deliverables
- Architecture audit
- Risk register
- Decision-ready brief
Phase 02
Build
Senior engineers build and ship the system end to end. You see working software every Friday. We write the deployment scripts and the documentation, not just the prototype.
Deliverables
- Production system
- Deployment and monitoring
- Runbook
Phase 03
Hand over
Your team owns it after we leave. We pair with your engineers, document everything, and stay on call until your team has completed two on-call rotations without incident.
Deliverables
- Handover documents
- Pairing weeks
- On-call backup
Note
Most engagements ship to production within twelve weeks. Where we cannot commit to a date with confidence, we say so on the discovery call, before anything is signed.
04AI engineering transformation
Help your team ship faster, with the team you already have.
We help engineering organisations move from traditional development to AI-augmented delivery, without rewriting the team or the codebase. A six-to-twelve-week programme that leaves your engineers shipping faster on the stack they already run, and your operations teams freed from work that software should be doing.
Best for Teams of 8 to 80 engineers, or operations teams reviewing where AI can replace manual workload
Lead time 6 to 12 weeks
01Pillar
AI-paired development
Roll out Cursor, Claude Code, and Copilot the right way: workspace conventions, prompt patterns, code-ownership rules, and the guardrails that keep velocity gains from turning into review debt.
02Pillar
AI-augmented testing and QA
Automated test generation, mutation testing, and AI-driven regression coverage that scales without growing the QA team. Coverage tied to what changed in the code, not to a fixed calendar.
03Pillar
Intelligent CI/CD
AI-assisted code review, pull-request triage, automated release notes, and security scanning built into the pipeline. Less time in meetings, more time shipping.
04Pillar
Engineering enablement
Training, internal playbooks, and pairing weeks that turn your existing team into AI-fluent shippers. The knowledge stays inside your company after we leave.
↓Cycle time
Days, not sprints
↑Review throughput
2–4× without adding headcount
↑Test coverage
Tied to the diff
↓Release lead time
Weekly to daily
Where to start
Most transformations move cycle time measurably within six weeks. We start with a two-week diagnostic to size the opportunity, calibrate the rollout, and agree the success metrics, before any tools are wired in.
Talk transformation05AI capabilities
AI that pays for itself.
We build production AI systems for businesses that need real returns: faster delivery, lower operating cost, leaner teams, and new revenue lines from the data they already own. Every capability below has been shipped to a paying client and is running in production today.
2–4×
Faster engineering throughput
With the team you already have
40–70%
Manual workload reduction
Across operations engagements
40–60%
Lower total delivery cost
vs traditional IT services firms
Move faster. Spend less. Keep the team lean.
01Capability
AI engineering transformation
For companies that already have a development team and want it to ship 2–4× faster. Through a six-to-twelve-week programme, your existing team adopts AI-augmented development end to end: how code is written, reviewed, tested, and released. Cycle times move from sprints to days. Review throughput multiplies without adding headcount.
2–4× throughput · zero net hiring
02Capability
Intelligent operations and workflow automation
Self-healing, monitored AI automations replace invoice processing, claims triage, CRM updates, appointment orchestration, document handling, and multi-system coordination. Entire coordinator roles have been redeployed in a single quarter, with no uptime regression.
60–80% workload cut · payback under 6 months
03Capability
AI workforce audit and cost optimisation
A three-to-four-week engagement that maps every repetitive workflow across operations, finance, HR, customer service, and sales. Each is scored by AI-replaceability, dollar savings, and implementation cost.
Quantified savings roadmap · executive-ready business case
Build AI products your competitors can't.
04Capability
Production AI products and copilots
Custom-built AI systems that solve your specific business problem. Internal copilots that turn institutional knowledge into a searchable asset, customer-facing AI features that differentiate your product, and intelligent assistants that handle the work juniors used to spend weeks on. Built to scale, monitored end to end, designed for your team to operate after handover.
Revenue-grade AI product live in 8–12 weeks
05Capability
Custom vision, language and predictive models
Where off-the-shelf AI does not fit, we build the model that does. Computer vision for quality inspection, medical imaging, and visual analytics. Predictive models for demand forecasting, lead-time prediction, churn, and risk. Custom language models trained on proprietary data and deployed on your own infrastructure.
Defensible moat · full IP ownership
06Capability
Data monetisation and new revenue lines
We analyse your first-party data, identify three to five new product lines or monetisation angles, prioritise by revenue against implementation cost, and produce a buildable specification for the highest-opportunity initiative.
Ranked roadmap · MVP spec · optional gain-share
07Capability
Fractional AI leadership
Senior AI strategy on retainer, for organisations between founder-led and a full AI function. Embedded senior leadership covering strategy, architecture reviews, vendor selection, build-vs-buy decisions, and hiring panels.
Chief AI Officer judgement at fractional cost
ProofAI projects shipped
Six engagements. All in production.
A representative cross-section. Detailed write-ups and live demos available under NDA on request.
AI 01Healthcare AI · India
Unified clinical AI platform for a high-volume IVF group.
Embryo grading, endometrial scoring, and WHO-compliant semen analysis in one platform; replaced four disconnected systems with a single source of truth for clinical decisions. Live since 2024.
Patients
10K+
Doc time recovered
40%
To production
11 weeks
AI 02Manufacturing AI · Italy
Production delay prediction for a global aluminium extrusion leader.
Machine-learning pipeline analysing order, job, and machine-level data to predict lead-time delays, so planners can act before a delay becomes a customer issue.
Accuracy (5-day window)
84%
Status
Production
Handover
Complete
AI 03Logistics AI · Sweden
Computer vision for warehouse digitisation in a WMS platform (€60M+ revenue, 30+ countries).
Custom CV pipeline reads warehouse CAD layouts, identifies racks and driveways, and generates production SQL to populate the WMS database, replacing around 50 hours of manual schema work per warehouse.
Layout accuracy
98.8%
Saved per diagram
~50 hrs
Status
Production
AI 04Operations AI · USA
Intelligent workflow automation suite for a multi-site dental operator.
Production automation across appointment orchestration, multi-channel CRM sync, insurance pre-authorisation, invoice processing, and document handling. Self-healing, with zero manual touch since go-live.
Workflows
15+
Manual effort cut
70%
Role eliminated
Coordinator
AI 05Energy ML · Sweden
Solar energy forecasting for a renewable energy operator.
LSTM forecasting model predicting daily solar energy production from meteorological data, integrated with a continuous-improvement feedback loop. Data infrastructure restructured to support continuous retraining and operational dashboards.
Model
LSTM time-series
Accuracy
Measurable gains
Status
Production
AI 06Insurance ML · Sweden
Claim propensity scoring for an insurance analytics firm.
Classification model predicting the likelihood of insurance claims, deployed into the firm's underwriting workflow. Continuous-improvement feedback loop in place so the model learns from every new claim closed.
Model
Classification
Accuracy
Measurable gains
Status
Production
06Selected work
Engagements that have shipped.
A representative cross-section. Detailed write-ups available under NDA on request.
Project 01Healthcare · Fertility
Patient platform for a high-volume IVF group.
Replaced four disconnected systems with a single clinician-facing platform. Reduced clinical documentation time by 40% in the first quarter after launch.
Patients served
10K+
Documentation time saved
40%
Time to production
11 weeks
Project 02Care · Compliance
Learning management system for a UK care-home group.
Consolidated training records, attestations, and audit evidence across 150+ facilities. Passed the first regulatory inspection cycle after rollout with no exceptions raised.
Facilities
150+
Certification completion
98%
Audit cycle
CQC-ready
Project 03Operations · Automation
Workflow automation for a mid-market services operator.
Moved fifteen recurring workflows from manual spreadsheets to monitored automations. Cut manual effort by 70% with no measured uptime regression.
Workflows
15+
Manual effort cut
70%
Uptime
99.9%
Project 04Health · Diagnostics
Standardised semen-analysis assistant aligned to WHO 6E.
Deployed an AI-assisted grading workflow across four reference labs. Inter-rater grade variance dropped to ±0.4 against the WHO 6th Edition gold standard.
Standard
WHO 6E
Grade variance
±0.4
Labs deployed
4
07What we measure
The numbers we hold ourselves to.
Self-reported metrics from our own engagement records, compared with publicly cited industry benchmarks where available.
Window 2023–2025
Sample 24 engagements
First-quarter retention of shipped systems
Share of engagements still in production 90 days after launch, with no major rewrite.
NEXUS96%
Industry61% (analyst benchmark)
On-time milestone delivery
Milestones delivered within the agreed window across the last 24 engagements.
NEXUS98%
Industry72% (industry typical)
Defect rate at handover
Production-severity defects per thousand lines of code, measured in the first two weeks after handover.
NEXUS0.4 / kLOC
Industry1.6 / kLOC (industry typical)
08In their words
What clients say after handover.
They wrote the spec, then ran the deployment. We never re-explained anything. The platform shipped in eleven weeks and is still our system of record.
Our engineers stopped asking when AI would help. Six weeks in, the workflow felt obvious. The retention metric we cared about moved 3×.
150 facilities, one audit cycle, zero exceptions. The platform replaced four spreadsheets and a contractor. We renewed before the warranty closed.
09Ways to engage
Four ways to work with us.
We agree the engagement on the briefing call and fix the terms in writing before any work begins.
AAI workforce audit
3–4 weeks · fixed fee
Map every repetitive workflow across operations, finance, HR, customer service, and sales. Each scored by AI-replaceability, dollar savings, and implementation cost.
Best for
Operators looking to identify where AI replaces cost before any build.
Output
Ranked, costed roadmap
BDiscovery sprint
2 weeks · fixed fee
Architecture audit, risk register, and a written technical brief.
Best for
Founders and CTOs deciding whether to build, buy, or rebuild.
Output
Decision-ready brief
CRapid build
8–14 weeks · milestone billed
Design, build, and ship a production system end to end.
Best for
Teams with a defined scope and a hard launch date.
Output
Live system and handover
DEmbedded partner
6–12 months · monthly retainer
Embedded engineering capacity, with an SLA-backed contract.
Best for
Operators running production systems who need ongoing build and on-call coverage.
Output
SLA-backed delivery
10Our delivery stack
The tools we ship with.
Production-tested, deliberately boring. We choose technology your team can hire for and operate after we leave.
Bias Operability over novelty
Maintained by Senior engineers
AI models and runtime
- OpenAIGPT family
- AnthropicClaude family
- GoogleGemini
- Mistral · LlamaOpen models
- vLLMSelf-hosted serving
- OllamaEdge inference
- LangChain · LlamaIndexOrchestration
Languages and frameworks
- TypeScript · JavaScript
- PythonML and APIs
- GoHigh-performance services
- Next.js · React
- React Native · ExpoMobile
- Node.js · Bun
- Tailwind CSS
Data layer
- PostgresPrimary database
- pgvectorVector search
- RedisCache and queues
- BigQuery · SnowflakeAnalytics warehouse
- KafkaStreaming
- ClickHouseReal-time analytics
- DynamoDB · FirestoreNoSQL
Infrastructure
- AWS
- Google Cloud
- CloudflareEdge and CDN
- Terraform · PulumiInfra as code
- Docker · Kubernetes
- GitHub ActionsCI/CD
- Vercel · NetlifyWeb platforms
Developer tools
- CursorAI-paired editor
- Claude CodeAgent-driven dev
- GitHub Copilot
- LinearProject tracking
- FigmaDesign
- StorybookComponent dev
- Playwright · VitestTesting
Observability
- OpenTelemetry
- Datadog
- Sentry
- Grafana · Prometheus
- PostHogProduct analytics
- LogRocketSession replay
Identity and auth
- Auth0 · ClerkHosted auth
- Supabase Auth · Cognito
- Okta · Azure ADEnterprise SSO
- SAML · OIDC · SCIM
- Passkeys · WebAuthn
Compliance toolchain
- HIPAA controls
- GDPR records and DPIAs
- SOC 2 evidence
- Audit trails
- Vanta · DrataCompliance automation
- 1Password · VaultSecret management
11Start a brief
Tell us what you are building.
Two paragraphs is enough. We reply within one business day with a recommended next step: a discovery call, a written brief, or an honest decline if we are not the right fit.
Channel Direct to founders
Reply ≤ 1 business day