Production-grade AI automation — shipped in weeks, not quarters.
We automate the workflows that cost your team hours every day — documents, intake, inboxes, reporting — with senior delivery, real integrations, and human-in-the-loop where it matters.
Six patterns we ship repeatedly
Each one is a proven shape — not a research project. We adapt the stack to your tools, not the other way around.
Document processing
The pain: PDFs, invoices, contracts, claims, lab reports stacking up in inboxes.
What we ship: OCR + structured extraction + validation pipeline that turns documents into clean data your systems can act on.
- Cut processing time 70–90%
- Audit trail per document
- Human-in-the-loop on edge cases
RAG assistants & internal Q&A
The pain: Teams hunting for answers across SharePoint, wikis, contracts, policies.
What we ship: Secure retrieval-augmented assistant that answers only from approved content, cites sources, respects access controls.
- Sub-2s answer latency
- Citations on every response
- No data leaves your tenant
Patient & client intake
The pain: Reception overload, paper forms, manual triage and insurance checks.
What we ship: Digital intake with field validation, insurance pre-check, and PMS / CRM sync — triage routed automatically.
- Reception load down 40–60%
- Fewer mis-routed cases
- Cleaner first-touch data
Email & message triage
The pain: Shared inboxes drowning support, ops or sales teams.
What we ship: Classification + routing + draft-reply generation, with confidence thresholds and human review on anything ambiguous.
- First-response time cut 50–80%
- Consistent tone & accuracy
- Backlogs cleared, not delegated
Reporting & operational dashboards
The pain: Analysts copy-pasting between spreadsheets to produce weekly reports.
What we ship: Replace spreadsheet reporting with structured pipelines and live dashboards — refreshed automatically, drill-down ready.
- Reports go from days to minutes
- Single source of truth
- Anomalies surfaced, not buried
Predictive ML & anomaly detection
The pain: Failures, churn, fraud or quality issues caught too late.
What we ship: Custom ML models trained on your data — anomaly detection, failure prediction, risk scoring with explainable outputs.
- Catch issues before they cost
- Explainable, auditable scores
- Retraining pipeline built in
What changes when we ship
Real workflows our clients run today — and how they ran before automation.
See what changes when workflows are automated
Switch industries and toggle between manual and automated flows.
Less reception load, fewer errors, faster patient flow.
Where we've already shipped
Intake, triage, PMS integration, claim workflows.
RAG assistants, structured intake, document analysis.
Invoice / receipt extraction, reconciliation, reporting.
Order ops, support triage, catalog & content automation.
Proposal generation, CRM hygiene, time capture.
Routing, exception handling, partner data integration.
From scoping call to scaled workflow
Predictable, thin-slice delivery. You see real value in production before committing to scale.
- 1Week 030-min scoping call
We map the workflow, the systems involved, and the cost of doing nothing. You get a written recommendation either way.
- 2Week 1Discovery & thin-slice plan
We sit with the team doing the work, document the as-is, and pick the one slice that proves value fastest.
- 3Weeks 2–4Build the thin slice
Senior engineers ship a production-grade slice — integrated with your systems, validated, with a human-in-the-loop where it matters.
- 4Weeks 4–6Pilot with real users
Roll out to a small group, measure, iterate. You see real numbers before committing to scale.
- 5OngoingScale & operate
Expand to adjacent workflows, harden, monitor. Optional managed support — or full handover to your team.
What we commit to
EU/CH hosting options, your tenant, your data. No training on your content.
Confidence thresholds and review queues — never silent automation on critical decisions.
We meet your stack — ERP, CRM, PMS, helpdesk, warehouse — not replace it.
Thin-slice delivery means real value in production fast, with room to iterate.
How automation-ready is your workflow?
Five inputs, no email required. You get a qualitative score and a suggested next step.
Automation Readiness Score
Five inputs. Qualitative score — no fake ROI numbers.
Several manageable steps can be automated to free meaningful capacity.
Selected AI projects
What AI clients say
Verified reviews from Clutch.
“They feel like a part of our company.”
Custom ML product for email marketing built on AWS, Node.js, Python and PyTorch — quality of services up 50%+.
“The product works well — agileful did a good job.”
Rewrote and improved a machine-learning prediction algorithm for press release monitoring, plus a SaaS user dashboard.
“They care about my metrics and success.”
Front- and backend MVP for turbine monitoring with simplified shop-floor UX and ML backend.
Questions we hear on the first call
How do you price an automation project?+
Fixed-price thin slice (typically 2–6 weeks), then a roadmap. No open-ended retainers, no vague monthly billing. You see scope and price before any work starts.
What about our data — does it leave the company?+
Default deployment runs in your tenant or on EU/CH infrastructure. We use models that contractually do not train on your data, and we scope access tightly. Compliance review fits in week one.
Do we need a clean dataset before starting?+
No. Part of the discovery is assessing the data we have to work with. Most projects start messy — the thin slice often surfaces what to clean first.
Who actually does the work?+
Senior engineers and a delivery lead — no offshored juniors, no 'AI strategy' theatre. You meet the people building it on the first call.
What if AI is overkill for our problem?+
Then we say so. About a third of the time the right answer is a simple workflow or integration, not a model. We bill the same either way — the goal is value shipped.
Book a 30-minute scoping call
We'll map your workflow, name the bottleneck, and tell you whether automation is the right call — in writing — either way.