INPUTS / QUERIES
// last 60 seconds
[10:42:01] classify invoice 2641-A
[10:42:03] retrieve policy §7.4.2
[10:42:08] draft reply · ticket #88421
[10:42:11] extract entities · contract
[10:42:14] reconcile ledger row
[10:42:17] route approval · €18,400
[10:42:19] summarize call · DE→EN

← illustrative trace
typical document workflow

OUTPUTS / ACTIONS
→ SAP invoice 2641-A · approved
→ Confluence answer published
→ Zendesk reply drafted · awaiting hum
→ Salesforce entities written back
→ NetSuite reconciliation queued
→ Slack approver pinged
→ Notion call summary attached

same 60s window →
7 systems written

POSITION · 01 OF 04

Most AI projects
die because they
never touch
the real system.

A model that answers questions in a sandbox is a demo. A model that reads from your Salesforce, writes to your SAP, respects your role-based access, fails over to a human when it should — that is an integration. We do the second thing. Not the first.

/ 01 — PATTERNS

Six integration patterns
we design and deploy.

Patterns · 06
All production-grade
01
Document-to-system agents

Invoices, contracts, RFPs, KYC packets, technical drawings. Extracted, validated, posted to the system of record — with confidence scores you can govern by.

SAP Oracle Workday
02
Customer-side copilots

Helpdesk and CRM-embedded assistants that draft replies in your voice, grounded in your knowledge base, with mandatory citation and clean escalation to humans.

Zendesk Salesforce Intercom
03
Internal company copilots

One assistant for the whole company — wired to SSO, your HR portal, your wiki, your code, your design files, your meeting transcripts. Permissioned, audited, yours.

Okta SSO Confluence Notion
04
Workflow & approval routing

Agents that read messages, decide what they are, where they should go, who should sign — and book the human in the loop when the rules say so.

ServiceNow Jira Slack
05
Edge & on-prem deployments

Local 7–70B models behind your firewall, on hardware you own, with no data leaving the perimeter. For finance, defence, healthcare and "no, really, no cloud".

vLLM llama.cpp NVIDIA H100/L40s
06
Evaluation & observability

The non-glamorous half: golden test sets, regression evals, online traffic shadow, cost dashboards, hallucination detection, drift alarms. Built before launch, not after.

LangSmith Braintrust Custom
/ 02 — ARCHITECTURE

A reference shape
for the work we actually build.

Diagram · v3.1
Last updated · 26.04
FIG.01 — Integration topology · simplified
L1 · SOURCES
SAP S/4HANA
Salesforce
Email · IMAP / Graph
Document store (S3)
Internal APIs
CSV / SFTP feeds
L2 · VERTO ORCHESTRATION
Retrieval & indexing
Routing & policy
Model gateway (private + hosted)
Tool / API call layer
Guardrails & eval
Audit & observability
L3 · DESTINATIONS
SAP postings
Salesforce records
Zendesk / ServiceNow tickets
Slack / Teams notifications
Human approval queue
BI / data warehouse
CROSS-CUTTING
SSO / RBAC Data residency PII redaction Rate limit / quota Cost dashboards Drift detection
DEPLOY TARGETS
AWS · EU regions Azure · sovereign GCP On-prem (k8s) Air-gapped
/ 03 — POSTURE

We have opinions
about which model and where.

Hosted frontier
Private weights · specialised
HOSTED FRONTIER

Claude · GPT · Gemini

For tasks where reasoning, code or open-ended writing genuinely matter. We route, cap, and meter — and we never let a tenant's data leave its region.

PRIVATE WEIGHTS

Llama · Qwen · Mistral

7B → 70B weights, deployed on hardware you control, on your network, with no external dependency. Fine-tuned where there's signal worth the cost.

SMALL & SPECIALISED

Classifiers · embeddings · OCR

The unsexy 80%: a small, well-trained classifier is almost always the right call before you reach for a 70B model. We prefer cheap correctness to expensive theatre.

POSITION · 04 OF 04

What we don't do.
Stated plainly.

  • ×Prompt-only "products" with no integration to anything real.
  • ×Vague pilots without an explicit kill criterion.
  • ×Avatar-faced chatbots that pretend to be people.
  • ×"AI" branding stitched over a small classifier.
  • ×Black-box systems your own engineers cannot reason about.
  • ×Models in production without an evaluation harness.
  • ×One-off demos that aren't on a path to a real workflow.
Q3 2026 · 2 slots open

Bring us
the workflow
you would
actually
measure.

We will tell you, on the first call, whether AI is the right tool for it. Sometimes the answer is no — a Python script, a better form, or 30 minutes with your data team is the honest answer. We will say so.

Book a 30-minute call Explore our capabilities