allgree.com
What we build

The whole product,
not one layer of it

Design, frontend, backend, mobile, infrastructure, and the AI parts, held by one team, so nothing falls into the gap between two vendors.

Talk to an engineer How we work
Practices
RetrievalAgentsEvaluationCost & latency

AI engineering

Most AI work fails between the demo and the release, not in the model. We build the parts that gap is made of: retrieval that returns the right documents, evaluation you can run on every change, cost and latency budgets, and a defined behaviour for when the model is wrong.

What that covers
Retrieval pipelines over your own documents, with citations
Evaluation sets and regression testing for prompts and models
Agent and tool-calling architectures with human review points
Voice, speech, and document processing pipelines
Cost, latency, and token budgeting per feature
Guardrails, fallbacks, and defined failure behaviour
Typically built with
ClaudeOpenAILangGraphLlamaIndexpgvectorPineconeWhisper
AI engineering, specifically

The work that starts after the demo

A model call is a few lines. What takes the time is retrieval quality, an evaluation suite, a cost ceiling per user, and deciding what the product does when the answer is wrong. These are the pieces we build.

Retrieval over your documents

Answers drawn from your own content, with a citation back to the source paragraph.

Task agents

Multi-step work with tool access, a step limit, and a human checkpoint before anything irreversible.

Document extraction

Structured fields out of invoices, contracts, forms, and IDs, with a confidence score and a review queue.

Voice interfaces

Inbound and outbound calling with interruption handling and a warm transfer to a person.

Speech pipelines

Transcription with speaker separation, custom vocabulary, and synthesis for the reply.

Support assistants

Conversation across turns, grounded in your help content, with escalation rules that trigger early.

Tooling

What we reach for

Defaults, not requirements. If your team already runs something that works, we learn it rather than argue for a rewrite.

Languages
  • TypeScript
  • Python
  • Go
  • Kotlin
  • Swift
  • SQL
Frontend
  • React
  • Next.js
  • React Native
  • Tailwind CSS
  • Vite
Backend
  • Node.js
  • FastAPI
  • Django
  • gRPC
  • GraphQL
Data
  • PostgreSQL
  • Redis
  • ClickHouse
  • Kafka
  • pgvector
  • S3
Infrastructure
  • AWS
  • GCP
  • Azure
  • Terraform
  • Docker
  • Kubernetes
  • GitHub Actions
AI
  • Claude
  • OpenAI
  • LangGraph
  • LlamaIndex
  • Whisper
  • Ollama
Observability
  • Grafana
  • Prometheus
  • OpenTelemetry
  • Sentry
Testing
  • Playwright
  • Vitest
  • pytest
  • k6

Not sure which of these you need?

Describe the problem instead of the solution. Working out which capabilities it needs is our job, and the first conversation is free.

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