Impressive demos rarely survive contact with operations.
Software that runs a whole workflow across your systems, with a person reviewing the exceptions. Built with the controls, governance and monitoring that keep it running in production.
Agent
Azure
Agents that complete real multi-step tasks across your systems, measured against the work they replace.
Close, reconciliation, and AP and AR workflows with audit trails.
Agents that resolve tickets end to end, with handoff to humans.
Read, classify and act on contracts, claims and filings.
Monitor, decide and act on exceptions across the chain.
An agent sits on your systems and your context layer, works inside guardrails, and hands a person anything it can't stand behind. It runs in your own cloud account on AWS, Google Cloud or Azure.
In your cloud accountIt reads what the task needs, applies your rules with code for anything that must be exact, and does the work: a draft, an update or a routed exception.
The agent reads incoming client documents, extracts the key entities and figures, and proposes how each maps into Exactera's data model.
Read the case study
An agent is software that works a task from start to finish: it reads the records it needs from your systems, decides each step against your rules, does the work, and hands a person anything it can't source or isn't sure about. In a Build engagement we pick one workflow, map every step and exception with the people who run it, connect the agent to your systems, write the rules and checks it runs against, and run it beside your team until its output matches theirs. Switch who does the steps below: the same order, a person at every step or one review at the end.
Software runs the repeatable steps; a person approves the one that does not match.
Foundation
Cloud
among othersMost teams start with one workflow that eats expert hours, not with a platform.
From our case studies, each figure as the study states it:
Reviewing a confidential information memorandum
Runs on
Agentic AI is easy to prototype and hard to operate. The gap between a demo and a system you can run in production is governance, reliability and the discipline to keep a human in the loop where it matters.
Approval gates, guardrails and escalation paths, so people stay in command of consequential decisions.
Evaluation suites, tracing and monitoring that prove an agent works, and keep proving it after launch.
Continuous checks with reviewable, defensible decision records.
We meet you at the right level of autonomy and progress deliberately, never shipping autonomy before the controls are ready.
Autonomous systems that plan and act across your operations, from task automation to multi-agent orchestration, deployed with human-in-the-loop controls, governance and production monitoring. The aim is agents that reach production, not demos: agents that complete real multi-step tasks across your systems, measured against the work they replace.
Four kinds. Finance and back-office automation: close, reconciliation, and AP and AR workflows with audit trails. Customer service agents that resolve tickets end to end, with handoff to humans. Document processing and extraction that reads, classifies and acts on contracts, claims and filings. Operations and supply chain agents that monitor, decide and act on exceptions across the chain.
With approval gates, guardrails and escalation paths, so people stay in command of consequential decisions. Evaluation suites, tracing and monitoring prove an agent works and keep proving it after launch, and continuous checks leave reviewable, defensible decision records. We never ship autonomy before the controls are ready.
Agentic AI is easy to prototype and hard to operate. The gap between a demo and a system you can run in production is governance, reliability and the discipline to keep a human in the loop where it matters. We meet you at the right level of autonomy and progress deliberately.
It depends on the workflow. Exactera's document agent was built in a four-week sprint, with experts reviewing its work from day one. Larger systems take longer, so we build one workflow first, run it beside the team until its output matches theirs, then widen.
Yes. Elara Caring's intake pipeline reads scanned referrals, extracts patient details and routes only the exceptions to a person, which cut referral-to-admission time from days to under 24 hours. Bregal Sagemount's sourcing system profiles and scores companies against the firm's criteria, 7x more researched a week. Exactera's document agent cut client data mapping time 60%. All three run at Level 3 (L3).