Recommendation Engine built by end-to-end engineers
Custom recommendation engines — product, content, and next-best-action — with A/B-tested lift.
What AI Recommendation Engine Development looks like with us
From scoping call to go-live, our Recommendation Engine engagements are designed for teams that care about what actually ships. Security and privacy are built in: NDA-first, least-privilege IAM, EU or US data residency, VPC-isolated deployment options. Every engagement starts with a mutual NDA, a scoping conversation with a senior engineer, and a written proposal within one week. All work product, source code, and documentation is assigned to you on payment — no vendor lock-in, ever.
- 01End-to-end automation: design, data pipelines, evaluation harness, deployment, observability
- 02Production SLAs — not a POC that collapses under real traffic
- 03Integrations with your existing systems (CRMs, ERPs, ticketing, data warehouses)
- 04Cost dashboards so you can see token/inference spend against ROI
- 05Re-training / prompt-tuning workflows documented for your team to own post-launch
How teams use this
Replace a manual process currently consuming 20+ hours/week of team time
Add AI to an existing product feature without rebuilding the whole workflow
Stand up a greenfield automation that your internal team will own post-handover
100+ companiesquietlyrunonsystemswebuilt.
Common questions
How do you measure success?
Every automation project has 2-3 written KPIs baked into the SoW — for example, time saved per case, containment rate, cost per transaction. We report against them weekly.
What about hallucinations and accuracy?
Every production LLM feature ships with an evaluation harness and confidence thresholds. Low-confidence outputs route to human review. We quote accuracy numbers against labelled samples, not vibes.
Who owns the IP?
You do. All code, documentation, model weights, and deliverables are assigned to you on payment. Our master service agreement spells this out explicitly.
Do you sign NDAs before a scoping call?
Yes — standard practice. We circulate a mutual NDA before any detailed conversation about your product, data, or roadmap.
Whatpeople who shipped with ussayafterwards.
Telluswhatyouwanttoautomate.We'llreplyinonebusinessday.
Describe the problem, the constraint, the deadline. We'll send back a scoped plan and a senior engineer to kick it off — no sales theater.