Agentic AI
Agents that plan, call tools, and hand work back to people.
- Multi-agent orchestration
- Tool use & MCP
- Human-in-the-loop
- Guardrails
- Workflow automation
Services
Thirteen services, one team.
We build the AI layer and the software underneath it — agents, voice, retrieval and models, on top of the product, data and infrastructure they need to run. Most engagements use three or four of these together, which is the reason they are in one place.
AI engineering
We start from what the system has to be right about, not from the model. A prompt, a retrieval pipeline and a trained classifier are three different answers, and picking the wrong one is expensive later rather than now.
Generative AI products
LLM features that hold up under real inputs.
- Copilots
- Document intelligence
- Structured extraction
- Prompt & context engineering
- Fine-tuning
Conversational & voice AI
Chat and phone agents that hold a real conversation.
- STT
- TTS
- Realtime turn-taking
- Telephony & SIP
- Multilingual
- +1 more
RAG & knowledge systems
Answers grounded in your data, with citations.
- Ingestion pipelines
- Embeddings
- Hybrid & vector search
- Rerankers
- Graph RAG
- +1 more
ML & computer vision
Models for the problems a language model is the wrong tool for.
- Forecasting & prediction
- Classification & ranking
- Object detection
- Segmentation & OCR
- Model serving
- +1 more
Product & platform
An AI feature is a product feature with a probabilistic middle. Somebody still has to own the schema, the deploy, the on-call rota and the bill — so we build that half properly, whether or not we built the model.
Product engineering
Web and mobile products, built to be maintained.
- Next.js
- React Native
- Design systems
- SaaS & multi-tenant
- Billing
- +1 more
Mobile engineering
Apps that feel native and ship on a predictable cadence.
- React Native & Expo
- Native Swift & Kotlin
- Offline-first sync
- Push & deep linking
- App store release pipelines
- +1 more
Backend & APIs
The services everything else depends on.
- FastAPI
- Node
- Go
- GraphQL
- WebSockets
- +2 more
Data engineering & analytics
Pipelines that make the AI worth having.
- ELT
- Streaming
- Warehouse & lakehouse
- dbt
- Data quality
- +1 more
Cloud, DevOps & platform
Ship it, run it, keep it cheap.
- AWS
- GCP
- Azure
- Kubernetes
- Serverless
- +4 more
Strategy, design & growth
The cheapest engineering decision is the one that stops a build. We would rather run a three-week feasibility spike and tell you the answer is no than spend six months arriving at it politely.
AI strategy & enablement
Work out what is worth building before building it.
- Opportunity audits
- Feasibility spikes
- Build vs buy
- Data readiness review
- Governance & policy
- +1 more
Design & product discovery
Decide what to build, and design it so people can use it.
- Product discovery
- Interface design
- Design systems
- Prototyping
- Designing for AI
- +1 more
Creative & growth engineering
Marketing surfaces built by the team that builds the product.
- Marketing sites
- Landing pages & experiments
- Technical SEO
- Documentation sites
- Analytics & attribution
- +1 more
How we work
The same five stages, whatever we are building.
Every engagement runs this way. The deliverable at the end of each stage is what you can hold us to, and it is the same list on a two-week spike as on a six-month build.
Discover
Frame the outcome, audit data and systems, spike the risky part, size it.
Design
Flows, interface, system and data architecture, agent and model design; prototype the riskiest path first.
Engineer
One-to-two week slices, CI from day one, instrumented as it is built, demo every sprint.
Evaluate & harden
Eval suites, red-teaming, guardrails, latency and cost budgets, load, accessibility and security review.
Launch & operate
Deploy, monitor, iterate on real usage, transfer knowledge.
Not sure which of these you need?
Most engagements start as one service and turn out to be three. Tell us the outcome you are after and we will tell you what it actually takes — including when the answer is that you do not need us yet.
contact@algologix.coWe reply within 24 hours.