Solutions

Outcomes, not buzzwords.

Four packaged solutions where we've shipped enough to know exactly how the next one will go. Pick one, ship in a quarter.

Enterprise Copilots

A copilot for the function that needs it most.

Sales, finance, ops, engineering, support — each function has a workflow that's 80% pattern, 20% judgement. We build copilots that automate the pattern and surface the judgement.

  • RFP / proposal copilot — drafts grounded in your win library and product catalog.
  • Engineering copilot — answers from your code, runbooks, and incident history.
  • Finance copilot — variance analysis, board-pack drafting, controller copilots.
Scope a copilot

TYPICAL OUTCOME · SaaS observability copilot

−47%
Mean time to first incident hypothesis

1,400
Engineers using daily within 90 days of launch

94%
Helpful-or-better rating in usage telemetry

CHANNELS

Web In-app WhatsApp SMS Slack Teams Voice (Twilio) Zendesk Salesforce

EVAL DEFAULTS

Resolution rate First-response accuracy Hand-off precision Jailbreak resistance

Conversational AI

Conversations that resolve, not deflect.

Chat and voice agents tied to your CRM, billing, and knowledge base. We design for resolution rate, not vanity engagement metrics — and we instrument the hand-off to humans more carefully than the bot itself.

Design a conversational system

Intelligent Document Processing

PDFs in. Structured decisions out.

Loan files, claims packets, contracts, prior-auth submissions, supplier invoices — the long tail of business runs on documents. We extract, validate, route, and decide — with citations on every claim and human review on anything below confidence.

  • Layout-aware extraction (tables, signatures, stamps).
  • Field-level confidence + human-in-the-loop queues.
  • Decision policies + audit trail per packet.
Talk to an IDP architect
PDF / TIFF / DOCX
↓ layout-aware OCR
Structured extraction · LLM + regex hybrid
↓ confidence scoring
High confidence → auto-decide Low → human queue
Decision + citations + audit log

SAMPLE USE CASES

  • Demand forecasting with explainable feature attribution
  • Churn / NRR modelling with LLM-driven cause narratives
  • Anomaly detection on operational and financial timeseries
  • Recommendation engines with reasoning-layer reranking
  • Risk scoring with policy + ML hybrid models

Predictive Analytics

Forecasts you'd defend in a board meeting.

Classical ML where it wins; LLMs where they win; and a reasoning layer on top that explains the forecast in business language. Every prediction comes with the features that drove it and the uncertainty around it.

Scope a predictive model

Have a specific outcome in mind?

Tell us what's broken. We'll tell you in 30 minutes whether it's a PoC, a platform, or a no.

Talk to an architect