AI automation services: agents that do the work, with a human still in charge

What you get with Speer

• Agents that complete a task end to end: intake, lookup, decision, action, record
• Document and data automation: classification, extraction and routing for claims, applications, invoices and clinical notes
• Integration with the systems that matter: EMRs, payment processors, property management platforms, ticketing and CRMs
• The control layer: permissions, human review, evaluation suites, audit trail and cost controls

What we automate

• Back-office workflows: intake queues, approvals, reconciliations and status updates that currently move by email and spreadsheet.
• Customer and resident requests: triage, drafting responses from your own policies and records, and routing to the right person with context attached.
• Document-heavy processes: reading forms, contracts and reports, pulling out the fields that matter and pushing them into the system of record.
• Engineering and IT operations: ticket enrichment, runbook execution with approval gates, and reporting.

How an automation project runs

1. Audit, two to three weeks: we map the workflow as it actually runs, measure the time and error rate today, confirm what data exists and where it lives, and rank the candidates by value and risk. You get a written plan.
2. Pilot, four to eight weeks: one workflow, real data, running next to the current process so the comparison is honest. A human reviews every output until the numbers earn trust.
3. Production: evaluation suites that run on every change, monitoring of output quality over time, per-task cost controls, rollback for prompts the way you roll back code, and governance documentation your auditors can read.
4. Expand: the second and third workflows reuse the integrations, permissions and review tooling from the first, so each one is cheaper and faster than the last.

What makes it safe to run

Every agent runs with the least access it needs, under a named service identity, with every action logged. Anything that affects a person, a payment or a record of consequence goes through a review step until the evaluation data shows it can be trusted, and some steps stay human permanently by design.

Production data stays in your environment. We develop against masked or synthetic data, encrypt data in transit and at rest, and build to HIPAA, PIPEDA, PCI DSS or SOC 2 requirements as your sector demands. Speer does not train shared models on partner data.

Model choice is an engineering decision, not a brand preference. We integrate hosted models from the major providers and open-weight models, behind an interface you can swap, and recommend retrieval over your own documents before any fine-tuning.

Why Speer

Speer has shipped 40+ digital products across healthcare, real estate, finance, entertainment and transportation, with a local team of 40+ engineers, designers and IP specialists. The same team that builds the automation handles the compliance work around it, which is where most automation projects stall.

Where an automation solves a technical problem in a new way, our IP specialists document it as it is built and work with patent counsel on protection, so the engineering spend becomes an asset you own.