Food manufacturing
Reading 40,000 supplier documents a month
Invoices, delivery notes and certificates are extracted, matched to orders and posted to the ledger.
Result 91% straight-through
Automate the work nobody wants to own.
We build AI that reads your documents, forecasts your demand and completes routine tasks in the systems you already run, with people approving what matters.
- Pilot live in 6 weeks
- Runs in your cloud account
- People approve risky actions
Capabilities
Six places AI pays for itself.
Pick the one closest to a real cost or delay. Each starts as a small pilot with a number attached.
Agents and copilots
Assistants that read your policies and systems, answer with sources, and hand over to a person when they are unsure.
See a similar project- Retrieval over your documents
- Tool use with approval gates
- Answer quality tracked weekly
Document intelligence
Turn inboxes and PDF folders into structured records, with confidence scores and a review queue for the doubtful ones.
See a similar project- Field extraction with validation
- Human review queue
- Direct posting to ERP or CRM
Forecasting and planning
Forecasts that explain themselves, refreshed daily from the data your planners already trust.
See a similar project- Backtests against your history
- Scenario comparison
- Alerts when drivers shift
Data platform
A clean, governed foundation so every model and dashboard reads from the same version of the truth.
See a similar project- Source-to-warehouse pipelines
- Data contracts and tests
- Cost-aware storage design
MLOps and monitoring
Release models like software: versioned, tested before launch and watched for drift afterwards.
See a similar project- Automated evaluation suites
- Staged rollouts
- Drift and cost dashboards
Governance and risk
Controls that satisfy your risk team and keep the work moving, mapped to the standards you already follow.
See a similar project- Model and prompt registers
- Role-based data access
- Audit trail for every decision
Payment run awaiting approval1,240 invoices, confidence 97%
3.1%sent to a person for review
Responsible by design
People stay in charge of what matters.
Automation should remove the dull work, not the judgement. Every system we build has a clear line between what it may do alone and what needs a person.
See why, every time
Each decision shows the source documents, rules and model confidence behind it.
Approval gates you control
Payments, deletions and customer messages wait for a named approver.
Earn autonomy with evidence
Thresholds loosen only when measured accuracy supports it.
How it works
From signal to action, in five steps.
The same loop runs behind every project we deliver. Select a step to see what it looks like in a live system.
Connect what you already have.
We connect to the systems your teams use every day, starting with read-only access, so nothing changes until you approve it.
sources 6 connected
mode read-only
latency nightly + events
No data leaves your cloud account
mode read-only
latency nightly + events
No data leaves your cloud account
Turn messy inputs into structure.
Models read documents, messages and records, extract the facts that matter and attach a confidence score to each one.
documents 41,230 / month
auto-accepted 91.4%
sent to review 8.6%
Every field links to its source
auto-accepted 91.4%
sent to review 8.6%
Every field links to its source
Apply your rules, then the model.
Business rules handle what is clear. Models handle what is fuzzy. Anything risky is escalated to the person who owns it.
rules 38 active
model calls 2,904 / day
escalations 3.1%
Thresholds are set by your team
model calls 2,904 / day
escalations 3.1%
Thresholds are set by your team
Complete the task in your systems.
Approved decisions post to your ERP, CRM or ticketing tool through audited connectors, with a rollback for each action.
actions 1,812 / day
failed 0.2%, retried
rollback available 30 days
Full log per action
failed 0.2%, retried
rollback available 30 days
Full log per action
Measure, correct and improve.
Reviewer corrections feed evaluation sets, so accuracy rises and cost per task falls. Reports go to the owner every week.
accuracy 96.8% (+2.1)
cost / task $0.07 (-31%)
drift none detected
Weekly report: Mondays 08:00
cost / task $0.07 (-31%)
drift none detected
Weekly report: Mondays 08:00
Results
Measured on three pilots, not on slides.
Averages across the first production quarter. Baselines were agreed with each client before work began.
73%fewer manual touches on invoice processing
4.2xfaster forecast refresh for the planning team
$1.8Mannual cost avoided across three production systems
Case studies
Two systems now in daily use.
Insurance
Triage for 6,000 claims a week
Claims are classified, enriched and routed to the right handler, with fraud signals shown beside each file.
Result 2.4 days faster first response
Governance
Built so your risk team says yes.
Controls are part of the design from week one, not a review at the end.
Evaluation before every release
Each model change runs against a test set built from your real cases, and results are signed off by the process owner.
People approve irreversible actions
Payments, deletions and customer messages wait for a named approver until the numbers earn more trust.
Runs inside your cloud account
Models, data and logs stay in your tenancy. We work through audited, time-boxed access.
A log for every decision
Inputs, model version, confidence and outcome are stored so you can answer why, months later.
Role-based access to sources
Each assistant sees only the data its job needs, enforced at the connector, not just in the prompt.
Drift and bias monitoring
We alert on shifts in accuracy, cost and fairness metrics, and agree the response before launch.
Technology
Open standards, your choice of vendor.
We recommend the simplest stack that meets the requirement and avoid lock-in to any single model provider.
Models and agents
- Claude
- Open-weight LLMs
- Gradient boosting
- Embeddings
Data
- Snowflake
- BigQuery
- dbt
- Airflow
Serving and MLOps
- Kubernetes
- MLflow
- Feature stores
- Evaluation harnesses
Integration
- SAP
- Salesforce
- ServiceNow
- REST and webhooks
Invoice matching used to take four people two days each month. It now finishes overnight, and the team reviews exceptions instead.
Elena VossFinance Director, Brightmoor FoodsWhat convinced us was the evaluation report. They showed exactly where the model was weak before we trusted it with a single customer.
Raj MenonHead of Risk, Corvane InsuranceEngagements
Start small, scale when the numbers agree.
Every engagement ends with a written result you can take to your board. Prices in US dollars.
Discover
Find the best first process to automate.
$12k
fixed fee, 2 weeks- Process and data audit
- Ranked list of opportunities
- Business case with savings range
- Risk and governance outline
Pilot
One process live in production, measured.
$45k
fixed fee, 6 weeks- Everything in Discover
- Working system for a small group
- Evaluation suite and dashboards
- Scale-or-stop decision report
Platform
Shared foundation for many automations.
Custom
scoped with your team- Governed data platform
- Reusable connectors and agents
- MLOps and monitoring
- Enablement for your team
FAQ
Straight answers on risk, data and cost.
Do we need clean data before we start?
No. The first two weeks include a data audit. Most pilots begin with the messiest, most manual process, because that is where the value is.
Will our data be used to train public models?
Never. Your data stays in your cloud account, and the models we deploy are not trained on it unless you explicitly choose a private fine-tune.
How do you keep the models from making costly mistakes?
Confidence thresholds, human approval for risky actions, and evaluation suites built from your real cases. We agree what must always go to a person before launch.
What does a pilot actually deliver?
One process running in production for a small group, with measured accuracy and savings, plus a plan to scale it or stop. You keep the code and documentation either way.
Can this work alongside our legacy systems?
Yes. Most of our connectors are to older ERPs, mainframes and shared drives. We add an integration layer rather than asking you to replace them.
Who owns the models and code?
You do. Everything is delivered into your repositories and accounts, with runbooks for your team.
Name the process. We will map the automation.
Describe one slow, manual process. In a 45-minute call we will sketch how it could run, what it would save and what could go wrong.
The mapping call is free and carries no obligation.