All four paths03 Workflow Automation · Mediforce

Agents that do the work
and pass the audit

Mediforce is our open-source platform for agentic workflows in regulated pharma. Define a process end to end, decide which steps a person runs, a script runs, or an agent runs, and get an audit trail on every run, out of the box.

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mediforce · workflow
PersonIntake & scope
AgentQuality assessment
ScriptStructural checks
AgentSummarize & flag
PersonReview & approve
Audit trail on every run
agentic workflow
#THE PROBLEM

Running agents safely inside a pharma org is harder than running them anywhere else. Access control, team permissions, auditability, and compliance have to come first, and most platforms either skip that layer or bolt it on after the demo wins the deal. So you spend months building infrastructure scaffolding before an agent touches a real workflow, or you ship something fast that breaks the moment QA asks how a decision was made.

#WHAT WE DO

A platform built for regulated agents

The platform

In Mediforce you define your process as a workflow, and every step is assigned to a person, a script, or an AI agent. Steps stay visible, trackable, and auditable. Autonomy is configurable per workflow: an agent can act on its own, or pause for human approval, and that is your call to make step by step, not a setting baked into the product.

The agents themselves are specialized components that each do one well-defined task: assess the quality of a data package, summarize a document, flag an anomaly. Because each agent does one thing, the same agent gets reused across different workflows. That reuse is where the value compounds.

Reusable use cases

On top of the platform, Mediforce ships pre-built workflow modules, including medical-monitoring triage, protocol-to-TLF, and a CRO data landing zone, with more in development. Start from a working module configured to your data and your process, or build your own with our team. Either way you skip the blank-slate phase that every project usually starts with.

Bring your own model

Mediforce is model-agnostic by design. Connect Claude, OpenAI, Gemini, or another provider through your own API key. No lock-in to a single vendor's model, and no waiting for the platform to support the one you want.

#WHY MEDIFORCE

Built for the part everyone else bolts on

Full auditability

Every step, every decision, every action is tracked and reviewable, built to meet the standards regulated work is held to.

Role-based access and human oversight

Different roles see different agents and different access levels. Agents act independently or wait for approval, configured per workflow.

Pharma domain knowledge

Built by a team that has shipped work for 8 of the world's 10 largest pharma companies. Mediforce reflects how pharma actually runs.

Bring your own model

Connect Claude, OpenAI, Gemini, or another provider with your own API key. Your choice, not ours.

#HOW IT WORKS

From regulated plumbing to scaled automation

01

Platform onboarding

Mediforce stands up inside your environment with your auth, your team structure, and your permission model, so the regulated plumbing is in place before any agent runs.

02

Pick the first workflow

Choose a process to automate, from the use-case library (medical-monitoring triage, protocol-to-TLF, CRO data landing zone) or a new one scoped with our team.

03

Configure agents and gates

Set each agent's scope, access, and review gates per role. Decide where a human approves, where the agent acts alone, and where it escalates.

04

Scale step by step

Move from one agent-assisted step to broader automation as the workflow earns trust. Never overnight, always with the audit trail intact.

#CASE STUDY

Pharmaverse package governance

Open source
Context

Pharmaverse is an open-source R consortium used by pharmaceutical companies.

Challenge

Hundreds of R packages in the ecosystem, with no systematic way to assess quality at scale.

Solution

A Mediforce agent evaluates each package's health and produces a structured assessment. A human council reviews that assessment and approves it or overrides it. The agent does the heavy lifting; the people keep final judgment.

Outcome

A live, public example of how Mediforce runs in a regulated environment, the same human-in-the-loop pattern that a clinical or statistical workflow needs, running in the open where anyone can see how it works.

Also in the use-case library — CRO data landing zone

A workflow detects incoming CRO data the moment it lands, runs structural and content checks against the study spec, returns flagged issues to the CRO, and notifies the internal team only when something needs human judgment. The same headcount handles more studies, with a full audit trail per file.

Use-case description, not a named client engagement.
#WHO THIS IS FOR

Who this is for

Teams running the workflows

  • Statistical Programmer II
  • Principal Statistical Analyst
  • Associate Director, Statistical Programming
  • Principal Biostatistician
  • Director

Leaders sponsoring the platform

  • Director, Statistical Programming
  • Senior Director, Clinical & Statistical Programming (Head, Technology Solutions)
  • Senior Director, Global Drug Development
  • Head of Data Science
  • Senior Principal Data Scientist & AI Product Lead
#VALIDATED AI

Mediforce is built to support validation, not to sit outside it. Every run produces the audit record a regulated process needs: inputs, outputs, the model version, the tools called, and the person who reviewed and approved each step. Human review is part of the workflow itself, and model versions are tracked to the granularity 21 CFR Part 11 calls for. Your team still owns validation. Mediforce gives them an environment built to make it pass.

Our Validated AI approach
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See Mediforce running on your kind of workflow.

Agentic workflows for regulated pharma: a person, a script, or an agent on each step, with an audit trail on every run.