AI Services · Build
AI agents that do real work, on data you can trust.
If the work follows a pattern and has a measurable result, we can build the agent for it. It answers, routes and resolves inside limits it can’t change, with your people approving what matters.
The queue is growing faster than the team
Customers wait for answers. Calls turn into voicemails, voicemails into callbacks, callbacks into missed appointments. Staff re-key the same data across several systems, and requests sit in the wrong inbox. The mandate from the top is to put AI to work this year.
The catch is that an agent is only as good as the data under it. Most companies’ data is scattered, duplicated and out of date. Gartner expects over 40% of agentic AI projects to be canceled by the end of 2027 over cost, unclear value or weak risk controls (Gartner). Demos are easy. Agents that hold up in production are engineering.
Agents we build
Customer service agents
Answer and resolve customer questions across chat and email from your own policies and records. Hand off to a person with the full context when they should.
Answering agents
Pick up calls, chats and web inquiries around the clock, then qualify, book and route them, so no lead or request waits until morning.
Workflow agents
Work a queue end to end under human approval: intake, triage, updates across your systems, follow-ups and exceptions.
Routing and efficiency agents
Classify, prioritize and route requests, tickets and leads to the right person, and flag work that’s stuck before a customer notices.
Knowledge assistants
Answer staff and customers from your own documents and data, cite their sources, and are built to decline rather than guess.
Sales and research agents
Watch sources for buying or risk signals, enrich and score them, and draft the outreach or alert for a person to send.
How you buy it
Automation Discovery
2–3 weeks · fixed fee
We map your processes and score each automation opportunity on value, risk and data readiness. We check what your existing software already does, and deliver an architecture and a costed roadmap. Right-sizing is included, for example a frontier model API instead of owned GPUs when that does the job.
Proof of concept on one workflow
about 3 weeks · introductory fixed fee for new clients
See it working on your own process before committing to a full build. One workflow, agreed success metrics from day one, and a path to production.
Agents built to your requirements
first agent 4–6 weeks · fixed fee
Each agent ships with an evaluation suite, a gateway-enforced cost ceiling, full traces, acceptance tests you approve and a kill switch. Each further agent reuses the foundation and costs less to build.
AI-ready data foundation
4–8 weeks · fixed fee · only when the roadmap calls for it
We audit the data your agents will depend on and fix it at the source. Then we build one clean, governed layer in your cloud that agents and reports read from.
Run and improve
capped monthly retainer per agent
Monitoring, exception queues, evaluation upkeep, model upgrades and a monthly cost review. Model usage passes through at cost.
A first live agent in about 6–9 weeks, when your data is ready
The path is 2–3 weeks of discovery, then 4–6 weeks to a first production agent. Where the roadmap calls for the data foundation, add 4–8 weeks. When the workflow is clear and the data is ready, a short scoping step can take you straight to a proof of concept. The data foundation comes in only where the roadmap shows an agent would otherwise be reading bad records.
Built to hold up in production
Data checked before agents rely on it
An agent is only as accurate as the records it reads. Discovery checks them, and we fix only what an agent will depend on.
Rules in code, judgment in the model
Code handles lookups, rules and calculations. The model handles language and judgment. Every figure of record comes from code, with a citation.
Measured always
Each agent passes its evaluation suite before launch and is scored in production, so you see accuracy and cost per task, not a demo.
People stay in charge
A person approves money movements and customer-facing actions until you choose to automate them. Every action is logged, every agent has a kill switch, and spending stops at the ceiling you set.
Our agents at work, with people signing off
130
fixes our agent fleet opened across 19 repositories in two days, most of them overnight, each merged after engineer review
1,400+
code-review items fixed by our AI fix agent on real pull requests, at as little as $0.09 each
8 of 8
known-bad dependency updates our dependency agent held back when replayed against 415 real updates
3.3%
of the SEC filings our monitoring pipeline reads reach an AI model; plain code screens the rest and does all the scoring
See it working
Our live demo runs on our own working governed environment. A knowledge assistant answers with citations and declines out-of-scope questions. A workflow agent pauses for human approval and has a kill switch. The gateway blocks personal data and enforces budgets. 30 minutes, no slides.
Questions operations leaders ask
Which industries do you build for?
Any business with high-volume, repetitive work: professional and field services, distribution and logistics, healthcare administration, finance and insurance operations, retail and software. What matters is the pattern in the work, not the sector.
Do we need perfect data first?
No. Discovery scores data readiness for each opportunity. Some agents can start on the data you have; others need the data foundation first, and the roadmap says which.
Will it work with our software?
Agents connect to the systems you already run, such as your CRM, help desk, phone and chat channels, scheduling and ERP. Connectors and channel adapters are part of the delivery.
Who owns the agent?
You do. Agents run in your accounts and your source control, documented so your team can run them.
Will you see our data?
Free assessments run on your side, under your credentials. For paid work, you approve in writing exactly what our engineers can access, and your data is not used to train AI models.
A free way to start
The Automation Opportunity Scan is a 20-minute online intake about your processes, tools and volumes. You get a ranked report. It shows which processes your software already covers, which are worth an agent, how ready your data is, and the hours each would save.
Tell us which work is piling up.
Describe the queue, the volume and the systems involved. We’ll tell you whether an agent fits and what it would take.