Services
Every AI service, delivered production-ready
From autonomous agents and automation to machine learning, computer vision, and the integration work that makes AI stick — pick a capability or tell us the outcome you need.
Capabilities
Our AI services
Each service stands on its own — and they compound when combined. Every engagement starts with the workflow where AI pays for itself first.
AI Agent Development
Custom AI agents that plan multi-step tasks, use your tools and APIs, and finish work end to end — with human approval gates where the stakes demand it.
AI Workflow & Business Process Automation
Intelligent automation for document processing, data entry, approvals, and back-office operations — AI where judgment is needed, deterministic code where it isn't.
Custom AI Software Development
Full-cycle custom AI development — from use-case definition through architecture, data, models, and deployment — for products off-the-shelf tools can't build.
Generative AI & LLM Application Development
Copilots, content generation, summarization, and structured extraction built into your product — with the prompt engineering and evals that make them dependable.
Enterprise RAG & AI Knowledge Assistants
Retrieval-augmented generation systems that let employees and customers query your documents, wikis, and databases in plain English — with cited, permission-aware answers.
AI Voice Agents & Conversational AI
AI voice agents that answer inbound calls, book appointments, qualify leads, and handle routine requests — natural to talk to, wired into your calendar and CRM.
AI Chatbot Development
Custom GPT-class chatbots for your website, app, and messaging channels — grounded in your content, able to take real actions, measured on resolution rate.
Machine Learning & Predictive Analytics
Forecasting, churn prediction, scoring, and anomaly detection models built on your data and deployed into the systems where decisions get made.
Computer Vision Development
Custom computer vision for quality inspection, object detection, OCR, and video analytics — deployed on the edge or in the cloud, tuned to your accuracy bar.
AI Consulting & Strategy
AI readiness assessments, use-case prioritization, and executable roadmaps from a team that ships AI to production — not slideware consultants.
AI Integration Services
Embed AI into your existing product, ERP, or CRM — Salesforce, HubSpot, NetSuite, and custom systems — without a rebuild or a rip-and-replace.
Choosing well
How to pick your first AI service
The wrong question is 'which technology is hottest?' The right one is 'which workflow, if automated, pays for itself fastest?' Three honest starting points, depending on where you are.
You know the pain, not the solution
Start from the workflow that hurts — the queue that never empties, the calls that go unanswered, the reconciliation that eats Fridays. Bring that to a scoping call and we'll map it to the right capability; you don't need to arrive knowing whether it's an agent, a model, or plain automation.
You have a shortlist of ideas
Rank them by two axes: how many hours (or how much leaked revenue) each represents, and how clean the underlying data is. High-volume plus clean data wins the first slot. We'll pressure-test the ranking on the first call and tell you if one is a trap.
You already have a build underway
If a prototype stalled before production — accuracy plateaued, costs surprised you, security review pushed back — that's an integration and hardening problem more than a rebuild. We regularly take over at exactly this stage.
Better together
Services that compound
A capability bought alone solves a task; capabilities combined remove a whole category of work. These are the pairings we see deliver outsized returns.
The knowledge-to-action stack
Retrieval grounds the agent in your real documentation and data; the agent turns those grounded answers into completed tasks. Companies that pair the two stop at far fewer 'the bot told me, now a human has to do it' hand-offs.
The front-door stack
Voice answers the phone, chat covers the website, and integration writes every interaction into your CRM and ticketing system — so no channel becomes an island of untracked conversations.
The back-office stack
Automation moves the paperwork; models score, forecast, and flag the exceptions worth a human's time. Together they shrink processing queues while raising, not lowering, the quality of what gets reviewed.
The de-risked start
A short strategy engagement ranks your workflows by payback before any build begins, then custom development executes the top of that list — so the roadmap is evidence, not a vendor's guess.
Delivery
One process behind every service
Whichever capability you buy, the discipline underneath is identical — because that discipline, not the model, is what separates systems that last from demos that don't.
Baseline before building
We measure the workflow as it runs today — volume, hours, error rates — so 'better' has a number attached from day one.
Architect against your systems
Integrations, data grounding, and security are designed against your real CRM, ERP, and data stores, not against a sandbox.
Demonstrate every sprint
You review working behavior and quality metrics in short increments, with the authority to redirect while redirecting is still cheap.
Operate and expand
Launch comes with monitoring, evaluation gates, and rollback plans — then the next workflow reuses everything the first one built.
The stack behind our services
- Claude (Anthropic)
- OpenAI
- LangGraph
- Model Context Protocol (MCP)
- Temporal (durable execution)
- TypeScript / Python
- Temporal / event-driven workflows
- n8n (where it fits)
- PostgreSQL / Supabase
- Claude (Anthropic) / OpenAI
- PyTorch / Hugging Face
- vLLM (self-hosted inference)
- PostgreSQL / pgvector
- AWS / GCP
- Python / TypeScript
- Vercel AI SDK
- LangSmith / Braintrust (evals)
- Structured outputs / JSON Schema
Tooling is chosen per engagement, not per fashion — and everything we configure is documented and handed over, so you're never locked to a vendor or to us.
Right-sized engagements
How big should your first engagement be?
Smaller than ambition suggests, bigger than a toy. The pattern that works: prove one workflow end to end, then scale on evidence.
One workflow, one metric
A single automation, assistant, or agent scoped to a measurable job — the right first step for most SMBs and for any team new to AI. Small enough to approve quickly, real enough to prove the model works.
A sequenced roadmap
Several connected workflows delivered in ROI order, sharing infrastructure, evaluation tooling, and integrations. Typical for mid-market companies ready to move beyond a first win.
Governed AI at scale
An agent platform or ML system with SSO, audit trails, private deployment options, and cost observability — built to pass enterprise security review and to be extended by your own teams.
Answers
AI services — common questions
Which AI service do I actually need?
Usually you don't need to decide up front. Describe the workflow — what comes in, what a person does with it, what should happen instead — and the capability follows: repetitive document flows point to automation, question-answering over internal knowledge points to RAG, tasks that require acting in other systems point to agents, and numeric predictions point to machine learning. A free scoping call settles it in under an hour.
Can we start with one service and add others later?
That's the recommended path. The integrations, evaluation tooling, and access controls built for your first workflow are reused by every workflow after it, so second and third builds are consistently faster and cheaper than the first.
Do you take over AI projects another team started?
Yes. Stalled prototypes are one of the most common starting points we see. We audit what exists, keep what's sound, and focus on the gaps that block production — usually evaluation, integration depth, and cost control rather than the model itself.
What if my problem spans several services?
Most real problems do — a support overhaul might involve RAG, a chatbot, voice, and CRM integration. Because one team covers all of these disciplines, you get a single architecture and a single accountable owner instead of stitching together specialist vendors.
How do you price these services?
First engagements are fixed-scope with an agreed success metric, sized to the problem — from focused SMB builds to enterprise programs. You'll see the cost, timeline, and definition of done in the proposal before committing to anything.
Do you only do AI, or software work around it too?
AI systems live inside ordinary software: APIs, databases, dashboards, cloud infrastructure. We build that surrounding layer as part of the engagement, so you're never left with a model and no way to run it.
Not sure where to start?
Tell us the workflow you want to automate or the product you want to build. We'll recommend the right approach — and the fastest path to ROI.