Technology
The stack we build with —
opinionated, durable, production-grade.
We pick technologies for the work, not for the demo. Here are the four areas where we go deep: generative AI, machine learning, blockchain, and IoT — each backed by shipped systems running in customer environments.
Generative AI
We build generative-AI products that hold up in production — grounded in your data, evaluated continuously, and instrumented for the failure modes that matter.
Retrieval-augmented generation (RAG)
Vector stores, hybrid search, re-ranking, and grounding — wired into your data with citations and access control.
Agentic systems
Goal-directed agents with tool use, planning, and verification — built to fail safely and explain themselves.
Fine-tuning and adapters
LoRA, QLoRA, instruction tuning, and preference optimization on open-weight models when accuracy or cost demands it.
Eval-driven development
Golden sets, regression harnesses, and online evals so model changes ship with measurable confidence — not vibes.
Machine Learning
Classical ML is still the right answer for most problems. We build forecasting, classification, ranking, and vision systems — and the MLOps to keep them honest after launch.
Forecasting and time series
Demand, capacity, churn, and anomaly forecasting on the messy, real-world data your operators actually have.
Classification and ranking
Triage, routing, prioritization, and relevance — calibrated to the cost of false positives and negatives in your business.
Computer vision
Detection, segmentation, OCR, and document understanding — deployed at the edge or in the cloud as latency requires.
MLOps and observability
Feature stores, model registries, drift monitors, and shadow deploys so the model in prod stays the model that was tested.
Blockchain
We pick blockchain when the trust model genuinely requires it — and engineer it accordingly. Audited contracts, clean wallet UX, and integrations that survive the next protocol upgrade.
Smart contracts and audits
Solidity and Move contracts written with explicit invariants, fuzz-tested, and reviewed against established attack patterns.
Tokenization and asset rails
On-chain settlement and tokenized asset workflows where verifiable provenance or cross-party trust is the requirement.
Zero-knowledge integrations
ZK proofs for privacy-preserving verification — used surgically, where the math actually pays for itself.
Wallet and identity UX
Custody, recovery, and signing flows designed for humans who do not want to think about block heights.
IoT & Edge
Connected hardware lives or dies on the unglamorous parts: telemetry, fleet rollout, and edge reliability. We build the boring layers so the product on top can be ambitious.
Device-to-cloud telemetry
MQTT, CoAP, and gRPC pipelines with backpressure, store-and-forward, and field-debuggable observability.
Edge inference
On-device ML for vision, audio, and sensor fusion — with OTA model updates and rollback safety.
Fleet management
Provisioning, secure boot, certificate rotation, and remote diagnostics for fleets numbered in the tens of thousands.
Industrial integrations
OPC UA, Modbus, BACnet, and CAN bus bridges into modern data platforms — without ripping out the PLC.
How we choose technology
Principles that hold whether the work is an AI agent or a Modbus bridge.
We pick well-understood foundations — Postgres, Kafka, Kubernetes — so the surface area where we innovate is the surface area that matters.
We avoid vendor lock-in by default. Your team owns the stack, the data, and the operational knowledge when we hand it back.
Structured logging, metrics, tracing, and evals are part of the original design — not retrofitted before the launch demo.
Threat modeling, secrets hygiene, and least-privilege access are built into the SDLC, not bolted on at audit time.
We design for the cloud bill you can defend in a board meeting — not for the demo that wins the RFP.
Runbooks, architecture diagrams, and on-call playbooks ship with the code. When we leave, your team has the keys.
Have a hard problem in one of these areas?
Send us the shape of the problem. We will tell you which of these technologies is the right hammer — and which ones are not.