AI Copilots
In-product assistants grounded in customer data with streaming, citations, and refusal logic.
Learn moreAI that survives production.
We ship the AI systems your engineers wish they had six months and a quiet sprint to build. Fixed scope. Named metrics. Your codebase, your cloud — measured before it ships and after.
support-copilot · prod
LIVE
JD
Why was my invoice charged twice last Tuesday?
AI
A retry hit our processor at 14:02 UTC after a timeout. The duplicate was auto-refunded within 4 minutes — no action needed.
billing.md#retriesincident-2148ledger.tx#9f3a
● grounded · 3 sources412ms$0.0008
Hallucinations
0.31%
↓ 87%
P95 latency
412ms
↓ 38%
Citation rate
99.2%
↑ 12pt
query > duplicate charge auto refund window
handbook/refund-policy.md0.94
…refund within 4 minutes…
ledger/transactions.sql0.88
…auto-reversal trigger…
runbooks/billing.md0.81
…duplicate retry guard…
Recall @5
0.96
↑ 0.18
MRR
0.71
↑ 22%
Chunk size
512
tuned
goal
Resolve duplicate-charge ticket end-to-end
plandecompose ticket✓
toolsearch · stripe.refunds✓
toollookup · customer.tier✓
actissue refund · $128.40✓
verifyledger reconciled✓
Steps / task
5.2
median
Auto-resolve
73%
↑ 41pt
Escalate rate
8%
↓ 19pt
Requests / min
4,128↑ 12%
us-east · canary 5%
P95 latency · last hour412ms
Error rate
0.04%
✓ SLO
Drift
0.02
stable
$ / 1k
$0.84
↓ 41%
Eval suite · golden set
47 / 47passing
v2026.05.17
Fine-tune loss · 12 epochs0.22
Tokens trained
84M
LoRA r=16
Win-rate
+18pt
vs base
Inference
$0.21
/ 1M tok
AI Copilots — grounded answers, with citations.
Trusted by
Helio
Lattice
Arden
Northwind
Vexor
Bryne
Quanta
Polaris
Kestrel
Mercato
Helio
Lattice
Arden
Northwind
Vexor
Bryne
Quanta
Polaris
Kestrel
Mercato
Why funded teams pick 47hq
The AI partner that ships, measures, and hands it back.
Most AI consultancies leave you with a demo and a deck. We leave you with a production system, named before/after metrics, and a runbook your on-call can act on at 2am.
Code in your repo. Inference in your cloud. Model- and infra-agnostic by default — so the next model release is your upside, not your migration.
300+
AI and cloud projects delivered
50+
VC-backed startups supported
$1.1B
Total valuation of VC-backed clients
Services
Three pillars. One delivery bar.
AI Implementation
From copilots to fine-tuned models — production builds your engineering team owns.
RAG & Embedding
Give your AI access to proprietary knowledge with scalable, hallucination-resistant retrieval.
Learn moreAI Agents
Production-ready agents with observability, tool integrations, and auto-scaling infra.
Learn moreDocument Processing
Process thousands of structured and unstructured documents — complex layouts, tables, and forms.
Learn moreFine-Tuning & Inference
Specialized models that reduce cost and improve accuracy for your domain.
Learn moreEvals & QA Framework
Golden datasets, CI gates, and LLM-as-judge rubrics that catch regressions before users do.
Learn moreHow we work
Five steps. No surprises.
Every engagement runs the same playbook — so you know exactly what happens before you sign, and exactly what "done" looks like.
- 01
Discovery
Free 20-minute intro call. We get specific about the problem, your success metrics, and your timeline — and tell you on the spot if we're not the right fit.
- 02
Diagnostic
Paid 60–90 minute working session against your live system. 12-point assessment delivered as a written 1-page diagnostic plus session recording within 48 hours.
- 03
Build
Fixed-scope Statement of Work with named deliverables and a single price. Senior engineers ship in your repo, your cloud, against your eval harness. Weekly demos, not status decks.
- 04
Ship
Production handoff: runbooks, golden eval sets, on-call rotation guide, and the rollback paths your team will actually use at 2am. Code lives in your repos from day one.
- 05
Metrics
Every engagement ships against 3–5 measurable outcomes — MRR, p95 latency, eval pass rate, cost-per-query — agreed in writing before we start. We don't bill the last invoice until they're hit.
Why teams pick us
What makes us different.
Diagnose before we prescribe.
Assessment-first, always
Every engagement starts with a 12-point diagnostic. We won't recommend a stack until we've measured the one you're on.
Scoped, not sold
Fixed scope, named deliverables, fixed timeline. If we can't define the win in writing, we don't take the engagement.
Work in any cloud
Deep depth in AWS, GCP, and Azure. We deploy where your data already lives — or migrate you cleanly when it doesn't.
Stack
Built on what your engineers already know.
Model-agnostic, cloud-agnostic, and fluent in the open-source tools that keep you off the vendor-lock-in treadmill.
Models
- OpenAI
- Anthropic
- Bedrock
- Vertex
- Llama
- Mistral
Retrieval
- Pinecone
- Weaviate
- pgvector
- Turbopuffer
- Mongo Atlas
Cloud
- AWS
- GCP
- Azure
- Cloudflare
- Fly.io
Orchestration
- LangGraph
- LlamaIndex
- Inngest
- Temporal
- Modal
Observability
- LangSmith
- Langfuse
- OpenTelemetry
- Datadog
- Grafana
Trusted by innovative companies
What our clients say.
"47hq's RAG expertise delivered our customer-requested proof of concept seamlessly. Their commitment to understanding our business made the collaboration both productive and enjoyable."
Peter Lebiedzinski
Founder & CEO, Printpal
"47hq's custom Bedrock AI solution saved us countless hours. The fine-tuned LLM dramatically streamlined our analysis process and was crucial in delivering a perfect fit."
Joshua Cohen
Founder & CEO, Tubefilter
"47hq's AI solution will save our customer service 50% time. They collaborated with our internal team and absolutely knocked the POC out of the park."
Fred White
Co-Founder, RentSecurely
FAQ
Real questions, technically answered.
- How fast can you start?
- Most engagements kick off within 1–2 weeks of a signed SOW. The discovery call is usually the same week you ask.
- Fixed-scope or time-and-materials?
- Default is fixed scope with named deliverables and a fixed timeline. Retainer or T&M only for ongoing reliability work — never for greenfield builds.
- Can we use our own LLM provider and vector DB?
- Yes. We're model- and infrastructure-agnostic. We've shipped against OpenAI, Anthropic, Bedrock, Vertex, self-hosted Llama — and Pinecone, Weaviate, pgvector, Turbopuffer, and Mongo Atlas.
- What happens after delivery?
- Engagements end with a written handoff package: runbooks, eval suite, on-call rotation guide. Optional monthly retainer. No multi-year MSAs.
Next step
Let's discuss your project. No sales pitch, just expert guidance.
Whether you're exploring AI possibilities or ready to scale to production, we'll help you navigate the path forward — from prototype to production.
Refundable if we're not a fitWritten diagnostic in 48 hoursSession run by a founder, not a sales rep