Leveret SystemsWe build the platforms that run your business
Custom software, system integrations, and data pipelines — built in weeks, not months. From replacing spreadsheets to full enterprise platforms.
What we do
Services
Each service below includes a live interactive demo — built from the same code and tools we use on real client projects.
From source file to factory floor
Real models translated through Autodesk Platform Services and recorded straight from the SVF2 viewer. Fusion, Revit, IFC, point clouds — the same pipeline, drives our customers' Bills of Materials, work orders and digital twins.
Who we are
The Team
We assemble the right team for every engagement — experienced practitioners across systems architecture, data analytics, software engineering, and digital marketing. Each project gets a dedicated team drawn from our network of specialists, led by a senior architect.
No bench warmers, no juniors learning on your project. Every team member is a practitioner with deep, hands-on experience in their discipline.
Systems Architecture & Development
20+ years experience
Enterprise platform design, full-stack development, system integration, and cloud architecture. Deep expertise in construction technology, manufacturing, and CAD-driven product lines.
Data Analytics & Business Intelligence
15+ years experience
Business analysis, BI development, data team leadership, and machine learning. Advanced qualifications including MSc Data Science. Track record at major enterprises in banking, telecoms, and fintech.
Software Engineering & DevOps
10+ years experience
Backend engineering, API design, CI/CD pipelines, and infrastructure automation. Experience across high-throughput platforms, real-time systems, and cloud-native microservices.
SEO & Digital Marketing
8+ years experience
Technical SEO, content strategy, and digital marketing across award-winning agencies. Sector expertise spanning e-commerce, travel, insurance, automotive, banking, and real estate.
Selected work
Case Studies
From 15 spreadsheets to one BigQuery-backed control plane — built from their own data, in six weeks
A growing bespoke manufacturer was running its entire business — sales, engineering, purchasing, and the factory floor — across disconnected Google Sheets and an under-used CRM. Sales couldn't see which quotes were converting. Engineers re-typed Bill of Materials data from CAD into purchasing sheets. The factory's source of truth was a single shared spreadsheet covering 16+ trade disciplines and 20+ live projects across four countries. Parts shortages were discovered the day before despatch.
Before · the pain
- Sales pipeline split across the inbox, a website quote-builder, the CRM, and Google Sheets — no unified view of any client
- 60,000+ historical emails containing orders, objections, and missed follow-ups that nobody could systematically read
- Bill of Materials data manually transcribed from CAD into purchasing sheets — typos caused parts shortages mid-build
- A single shared planning spreadsheet was the entire factory's source of truth: 16 trade disciplines, 20+ projects, no real-time view
- Parts coverage tracked in a separate workbook; shortages discovered days before despatch deadlines
After · centralised on GCP
- One BigQuery warehouse stitching GA4 sessions, website quotes, inbox, CRM, Xero, and CAD — every business surface joined on the customer record
- An AI agent (Claude Haiku + Sonnet) classifies every incoming email — intent, entities, sentiment, suggested reply — and surfaces missed opportunities in the dashboard
- Bill of Materials data auto-extracted from CAD via Autodesk APS, normalised in the parts library, and pushed to the factory app — engineers stop re-typing
- A factory-floor PWA replaces the planning spreadsheet: real-time work orders, 8-gate pipeline, daily photo progress, offline queue when the wifi drops
- A Coverage Tree across 20+ live projects shows every part's allocation, what's on PO, and what's short — surfaced before it becomes a delivery risk
Systems built · what powers the transformation
all on GCP · OAuth-gated · BigQuery-backedSales Dashboard
liveFlask + BigQuery sales-intelligence workbench behind Google OAuth. Five surfaces: What's Working, Pitfalls, Client Journeys, Planning, Catalog. ~78 API endpoints, Xero actuals overlay, probability-weighted pipeline forecast.
Catalog Dashboard
liveProduct-master workbench: AI-generated descriptions, 3D model extraction via Autodesk APS, normalised parts library, draft/approve/publish workflow, auto-generated compliance spec sheets.
Manufacturing PWA
liveFactory-floor PWA replacing the planning spreadsheet. Projects, work orders, 8-gate discipline pipeline, daily photo progress, offline queue (IndexedDB), role-based UI (worker / lead / admin), live SKU picker auto-fills the Bill of Materials.
GCP Substrate
liveEverything centralised: BigQuery warehouses, GCS buckets for photos / metadata / spec sheets, a Windows VM running the CAD Document Manager for assembly pack-and-go, Autodesk APS for SVF2 translation. Deploy from master, OAuth-gated, secrets in env.yaml.
For the factory floor
Automation does the repetitive, error-prone work
- Operatives open the PWA on a tablet — see today's work, capture progress photos, update the gate, log hours; works offline and syncs when reconnected
- SKU picker auto-fills the work order name, documents, and Bill of Materials from the published catalogue — no manual re-entry
- Daily photos are publicly URL-addressable in GCS; the daily progress banner shows the day's outputs across the team
- 8-gate pipeline (DSGN → GARV → MTRL → LASR → … → SHIP) is visible per work order — everyone knows what's blocking what
For management
BI you can actually act on — every system unified
- Live Coverage Tree: every part across every project, % allocated, unallocated £, on PO, days-to-deadline — one click to drill into any project
- Pipeline forecast with probability weighting, Xero actuals overlay, cycle-time analytics, win/loss heatmap by product and country
- Missed-opportunity report from the AI email agent — quotes with no follow-up, deals presumed lost, recovery scenarios
- Per-project work-order progress with photo evidence, hours booked vs estimate, materials status — a director can audit any project in 60 seconds
Deliverables
AI in production
Six AI agents shipped — running every day, in production
Not demos. Not chatbots. Real production agents reading our clients' data and writing actions back into their stack — email inboxes, Revit models, supplier feeds, customer journeys, internal PRs. Built with model routing, retries, observability, and hallucination guards. Two-pass pipelines (Haiku triage → Sonnet depth) keep cost down without losing accuracy.
Email Triage Agent
Two-pass classification on every inbound — intent, sentiment, entities, draft reply.
Revit Element Classifier
Native Revit properties + position rules → 38 derived element classes.
Supplier Risk Forecaster
Predicts slip risk per supplier from historical lead-time variance + live signals.
Customer Journey Stitcher
Unifies every GA4 session, quote, email and CRM event per customer — semantic match.
Quote Draft Assistant
Turns a customer enquiry into a draft quote with line items priced from catalogue.
Internal Dev Copilot
Reviews every internal PR against codebase conventions + flags risky migrations.
AI engineering
How we keep AI consistent in production
LLMs are extraordinary at reasoning, synthesis, and finding needles in haystacks of unstructured data — but on their own they're inconsistent and burn tokens. We build them inside a three-layer hybrid stack: deterministic rules narrow the haystack, ML ranks the candidates, and the LLM does the novel reasoning at the end — always with citations, schema-validated outputs, and full observability.
Architectural principles
01Hybrid: rules + ML + LLM
Determinism where it matters (PK lookups, validation, scope filters). ML for forecasting and ranking. LLM only for novel reasoning and synthesis. The right tool per task — never a hammer for every nail.
02RAG with citations
Vector search over your own data + LLM synthesis. Every claim cites the source row, document, or chunk. The model can't fabricate — it can only retrieve and combine. If the data isn't there, the agent says so.
03Two-pass cost optimisation
Haiku triages cheap and fast — 80% of cases never touch Sonnet. The deep model only sees what genuinely needs reasoning. ~4× cheaper without losing accuracy. Per-inbound cost: pennies.
04Structured outputs · function calling
JSON schemas enforced at the model boundary. Function calling so the model returns tool invocations, not prose. Downstream code never parses free-text — fewer surprises, easier rollback.
05Hallucination guards
Output validated against schema. Citation requirement on every claim. Confidence thresholds — low-confidence outputs route for human review, never auto-commit. Drift detection on output distributions.
06AI as the orchestrator, not the worker
The LLM chooses which rule to apply, which ML model to consult, which dataset to query. It steers the stack and reasons over outputs — it doesn't replace the deterministic plumbing underneath. Reasoning > replacement.
Engagement
Pricing
Flexible engagement options to match your project scope and budget.
Day rates
Indicative project pricing
Industries
Sectors
Construction & AEC
BIM/CDE integration, ISO 19650, Autodesk APS, digital engineering
Manufacturing
Production planning, quoting systems, inventory and pricing management
Utilities & Infrastructure
Asset management, OT/IT integration, digital twin platforms
Professional Services
Client portals, document automation, workflow management, CRM
SMEs & Scale-ups
Replacing spreadsheets and manual processes with custom platforms
Process
How we work
Discovery call
We understand your problem, systems landscape, and goals.
Architecture & scope
A clear proposal with architecture, timeline, and fixed or day-rate pricing.
Build
Iterative delivery with weekly demos — you see progress from week one.
Launch & support
Deployment, training, documentation, and ongoing support options.
Get in touch
Start a conversation
Whether you have a specific project in mind or want to explore how automation could help your business, we would love to hear from you.