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AI Integration

Ship AI features your users actually use.

Embed AI into your product — chat, semantic search, generation, classification, and RAG — with the evals, latency, and UX your users expect.

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4–8 wks
Avg. AI feature ship time
< 2s
p95 latency target
pgvector · Pinecone · Turbopuffer · Weaviate
Vector DBs supported

Why teams hire us for ai integration

Shipping an AI feature is easy. Shipping one your users love — fast, accurate, trustworthy — is where most teams stall.

We partner with product and engineering teams to design, build, and ship AI features inside real products: chat, search, writing, classification, and RAG experiences.

We bring a point of view on UX, evals, streaming, latency, and cost — so your feature ships well, not just ships.

AI Chat & Assistants

In-app chat and copilot experiences grounded in your data, with streaming, tool use, and memory.

Semantic & Hybrid Search

Vector + keyword search with reranking for product catalogs, help centers, and internal knowledge.

RAG Pipelines

Chunking, embedding, indexing, retrieval, and eval pipelines on pgvector, Pinecone, Turbopuffer, or Weaviate.

Generation Features

Drafting, rewriting, summarizing, and transformation features with prompt and structured-output engineering.

Classification & Extraction

Categorization, tagging, PII extraction, and structured-data extraction at scale.

LLMOps

Evals, A/B tests, prompt versioning, cost monitoring, and fallback routing with Braintrust, Langfuse, or Helicone.

What you get

Deliverables

  • Feature spec + UX prototypes
  • RAG / prompt pipeline
  • Streaming UI integration
  • Evals + observability
  • Cost + latency report
  • Enablement for your team
Fit check

Ideal for

  • SaaS teams launching their first AI features
  • Established products adding a copilot or search layer
  • Marketplaces, knowledge tools, and content platforms
Process

How we ship ai integration

01
Spec

Define the feature, success metrics, and UX.

02
Prototype

Ship a working prompt + retrieval pipeline.

03
Integrate

Ship inside the product with streaming UX.

04
Harden

Evals, cost, latency, and observability.

FAQ

Questions, answered

No — we embed. We pair with your engineers, follow your standards, and hand off clean code.
Evals on a labeled set, offline + online A/B tests, and user satisfaction feedback loops.
Yes. We support private model deployments, BYOK, and region-pinned vector databases.

Let's build your ai integration engine

Book a 15-minute intro. If we're not a fit, we'll tell you in the call — and point you to someone who is.