AI automation and integration services that connect your tools, automate workflows and ship measurable outcomes. Built by engineers, not prompt jockeys.
We design and ship practical AI automations and integrations for teams that need measurable outcomes, not slideware. From workflow automation to LLM-powered features inside your existing tools, we build the glue that makes AI useful in production.
The pain points we hear every week from product, ops and revenue teams.
CRM, ERP, support and data live in silos. Humans copy-paste between them.
Triage, qualification, data entry and reporting eat the team's best hours.
Prompt demos look great in a notebook, then die on the way to production.
You need EU data residency, audit trails and clear guardrails on AI usage.
Pick a sharp engagement or combine them into a roadmap. Pricing on assessment.
A short, focused engagement to map your workflows, score AI opportunities by ROI and risk, and deliver a pragmatic roadmap.
End-to-end automations that connect your CRM, ERP, helpdesk and data warehouse, with LLMs in the loop where they earn their keep.
Ship AI features inside your product or internal tools: copilots, semantic search, summarization, and Retrieval-Augmented Generation over your own data.
Production-grade agents with tools, memory and safety rails: research, support, sales-ops and back-office tasks executed reliably.
Reliable integrations between SaaS, internal APIs and data platforms. Webhooks, queues, ETL/ELT and reverse-ETL, properly engineered.
We run, monitor and improve your AI workflows: drift detection, evals, prompt iterations, cost optimization and on-call.
High-leverage use cases we ship repeatedly.
Lead enrichment, qualification, routing and CRM hygiene.
Ticket triage, suggested replies, knowledge-base RAG.
Natural-language analytics over your warehouse.
Invoice parsing, reconciliation, document workflows.
Product enrichment, search, personalization, content ops.
RAG over your wiki, code, contracts and SOPs.
Vendor-neutral. We pick the right tool per use case, not per slide deck.
Grouped by theme to help you find the answer faster.
Start with the AI Opportunity Audit. In 1 to 2 weeks we map workflows, score opportunities by ROI and risk, and tell you honestly what to automate, what to integrate, and what to leave alone.
Most engagements run 4 to 10 weeks: discovery, prototype, productionization, evals and handover. We work in two-week iterations with weekly demos.
No. We bring the engineering. If you already have a data team, we slot in alongside them and follow your standards.
We're model-agnostic: OpenAI, Anthropic, Google, Mistral, Llama and open-source models on your own infrastructure. We route per use case based on cost, latency and quality.
Yes. We deploy and operate open-source LLMs on your cloud when data residency, cost or control require it, alongside our Kubernetes practice.
Standard practice. We design ingestion, chunking, embeddings, retrieval and evaluation, with pgvector or managed vector databases depending on scale.
Anything with an API or database: HubSpot, Salesforce, Zendesk, Intercom, Shopify, SAP, NetSuite, Microsoft 365, Google Workspace, Snowflake, BigQuery, Postgres and custom internal services.
When they fit. For fast wins and ops-owned flows we use n8n, Zapier or Make. For high-volume, mission-critical workflows we build typed, tested code with proper CI/CD.
Yes. We embed copilots, search and summarization directly into your app via your existing frontend and backend, with feature flags and gradual rollouts.
We default to EU regions and providers that contractually keep your data inside the EU. Self-hosted models give full control when required.
No. We only use enterprise tiers and API endpoints with no-training clauses, or fully self-hosted models.
We minimize, redact and tokenize sensitive fields at the boundary, use secret managers, and keep full audit trails on AI calls.
Model routing, caching, batching, smaller fine-tuned models where possible, and per-feature budgets with alerts. We treat tokens like cloud cost: monitored and optimized.
Continuous evals against golden datasets, regression tests on prompt and model changes, and product metrics tied to the business outcome.
Yes, via Managed AI Operations: monitoring, evals, model updates, prompt iterations and on-call, on a monthly retainer.
Tell us about it. We'll come back with an honest take and a sharp proposal, usually within 48 hours.
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