The end ofmanual work.
Turn a costly workflow into a focused AI project. We help you assess the opportunity, build the system, and evaluate it against the work it needs to do.
Four scripted examples show an invoice discrepancy, a month-end close, an acquisition diligence finding and a logistics pricing opportunity. Each follows the inputs, reasoning, exception and outcome. Systems, amounts and results are illustrative, not live activity or client results. Use the play or pause control to manage the animation.
Capabilities
We do not sell off-the-shelf software. We engineer bespoke intelligence.
Reasoning Engines
Agents that read, reason, and resolve. From complex document analysis to automated support triage.
- Financial Reconciliation
- Audit & Compliance
- Contract Analysis
Adaptive Optimization
Systems that don't just predict the future, but adapt to it. We build control loops for volatile environments.
- Dynamic Pricing
- Supply Chain Resilience
- Capital Allocation
Intelligent Infrastructure
The plumbing for autonomous enterprise. We turn messy, unstructured data streams into structured, actionable events.
- Unstructured Data Extraction
- Multi-Agent Orchestration
- Automated Reporting
The last mile of intelligence.
A strong model is easy to get. A system your team can trust is what we build: the data it draws on, the systems it lives inside, the rules it keeps, and how it improves.
Build only the part that's yours
We look for the part that is yours — the records nobody else holds, the judgment calls your best people make on instinct, the step where the process breaks — and put the engineering there. Where a standard model already does the job, we use it.
Work inside the systems you already run
The workflow already lives somewhere — an ERP, a spreadsheet three people understand, handoffs nobody wrote down. We build to those, settle early what the system may read and change, and roll out in stages with the old process kept in reach.
Put the rules in code
A model works in probabilities; a credit limit does not. Approval thresholds, what the system may never share, what needs a signature: these live in testable code around the model. Its actions are bounded, low-confidence cases go to a reviewer, and we log what it does.
Get better on purpose
The system will get things wrong. We make errors easy to spot and correct, route each correction through a reviewer and then into the data, the rules, the prompts, or the model, wherever the fault lives. Changes are tested before they reach everyone.
Decision Library
Start with the exact decision you need to make.
Three kinds of guide, one job: helping you decide. Use cases show where AI belongs in a workflow, playbooks how to get from pilot to production, comparisons which stack, model, and build choices are worth the tradeoff.
Start with one workflow.
Tell us which process takes the most time, where it breaks, and what a better outcome would look like. We can help define a focused first project.
Discuss a project→hello@sophon.consulting