Custom AI Agency for Pharma: Agency, Platform or In-House?
A custom AI agency for pharma designs and builds AI tools around a company's own marketing workflows, data and compliance rules. Before hiring one, decide whether you need an agency, a platform you configure or an in-house build, since each puts ownership somewhere different. Whichever you choose, the build must draw only on approved sources, send work through MLR review, keep an audit trail, meet your security bar and sign a BAA where health data is involved. Here's how to decide, and how Nagent works for pharma teams.
What does a custom AI agency for pharma do?
An agency that builds custom AI for pharma marketing usually runs a discovery phase, maps where AI could help, then builds and hands over tools such as:
content drafting from approved claims and references;
variant generation for markets, channels and audiences;
pre-checks that catch issues before medical, legal and regulatory (MLR) review;
HCP and patient email programmes;
search and answer engine content for disease awareness;
reporting that pulls data from several systems into one view.
The value is fit: the tools are shaped to your brands, your markets and your review process. The risk is what happens after handover, when the agency's team moves on and yours has to run, maintain and update what was built.
Agency, platform or in-house: which is right for pharma?
Option: Custom AI agency, Who builds: The agency's team, Who runs it after launch: Your team, or the agency on retainer, Best when: The workflow is unusual and you have budget for a bespoke build
Option: Platform, Who builds: You configure, the vendor maintains the core, Who runs it after launch: Your team, on the vendor's product, Best when: Your needs match common marketing work and you want governance built in
Option: In-house build, Who builds: Your engineers, Who runs it after launch: Your engineers, Best when: AI is strategic, you have the engineering team, and you accept the maintenance load
Option: Platform plus engineers, Who builds: The vendor's engineers build on the platform, Who runs it after launch: Your team, on the same platform, Best when: You want custom fit without owning a bespoke codebase
Three questions usually settle it:
Is the work common or unique? Drafting, variants, email and reporting are common across pharma marketing. A unique workflow, such as a tool tied to a proprietary data asset, leans toward a custom build.
Who will own it in a year? If nobody on your side can maintain a bespoke tool, a platform with the vendor maintaining the core is safer.
Where do governance and audit live? A platform should bring approvals, audit and access control with it. An agency build has to create them, and you have to check they work.
What must a custom AI build for pharma include?
Whoever builds it, these are not optional in pharma:
Approved sources only. The AI should draft from your label text, approved claims, references and brand guidelines, and leave a gap for a person rather than fill it from general knowledge.
Rules that travel with every draft. Banned phrases and mandatory statements enforced as rules, not left for reviewers to catch.
An MLR gate. Every piece goes through your existing review process. The build prepares work for MLR; it doesn't approve it or create a side door around it.
A named person before anything goes out. Publishing, sending and any live change wait for approval.
An audit trail. Who drafted, who reviewed, who approved and why, kept in a form an auditor can read.
Security and data terms. Tenant isolation, role-based access, data residency, the certifications your procurement team asks for, and a business associate agreement (BAA) where protected health information may be involved.
Clear limits. Medical judgement, claim approval, adverse event decisions and anything near off-label promotion stay with qualified people.
A plan for change. Labels and guidelines change. Someone must own updating sources and rules, and finding content a change affects.
What questions should you ask a pharma AI agency?
Ask every agency, platform vendor or internal team the same questions, and ask to see answers working, not described:
Where does the AI get its facts, and what does it do when your approved sources don't cover a topic?
How are banned claims and mandatory statements enforced? Show a draft that breaks a rule and what happens to it.
How does the build hand work into our MLR system? Who is the system of record for approval?
What can the AI do without a person? Show the approval step for anything that publishes, sends or spends.
What is recorded, and can we export it?
Which certifications are held and which are in progress? Ask for the certificate, not the logo.
Will you sign a BAA, and where will our data be hosted?
Who maintains the build after launch, and what does a change to a source or rule cost in time?
What do we own at the end? Code, prompts, configurations and data.
Who on your team has worked within pharma promotional rules? Ask how they handled MLR feedback on a past build.
An agency that promises automated compliance or MLR approval is selling something no tool can deliver. Compliance comes from the content and the review.
Is Nagent a custom AI agency for pharma?
No. Nagent is a platform, not an agency. Nagent is multiplayer AI for growth: people and AI agents in one shared context, delivering the number. It gives you a growth org of AI teammates for Marketing, Sales and Content, led by MIRA, the AI Marketing Chief of Staff, SERA, the AI Sales Chief of Staff, and CREA, the AI Content Chief of Staff, with your people working beside them in one workspace. Where your plan includes it, a Nagent marketer joins your team and owns the number with you.
For pharma teams that want custom fit, Nagent offers three routes, all on the same platform:
Build your own agent. In Agent Workbench, you describe the job in one sentence. The agent builder asks a few questions and drafts the whole agent for you to review, including its tools, triggers, guardrails, model, autonomy level and system prompt. Nothing exists until you press Provision agent. See creating an agent.
Enterprise custom work. The Enterprise plan includes custom agents, workflows and integrations, plus VPC deployment and bring your own model and key. Through Nagent AI Labs, forward deployed engineers run a discovery sprint, then build custom agents on the Nagent platform alongside your team.
Ready-made teams. For common work, CREA's Content team drafts from your Knowledge Hub and brand book, and FOLIO carries the banned claims and mandatory items from your guidelines into every long-form publication.
The governance comes with the platform rather than being built per project:
Earned autonomy. Every agent arrives at L2 Assist, where it drafts on its own and waits for a person before changing records others rely on. A person, never the system, raises a level.
Approvals and audit. Nothing publishes without a person approving it, and every change to what an agent may do is recorded with who made it and why.
Security. ISO/IEC 27001:2022 certified by InterCert, with a SOC 2 Type II programme underway. Tenant isolation, role-based access, append-only audit and private VPC are available today. HIPAA is in process, and a BAA is available for healthcare customers.
Nagent is not an MLR system and does not handle adverse event reporting. Its drafts go into your existing review process. The pharma and healthcare page shows how the growth org works for pharma teams.
How should a pharma team start a custom AI project?
Pick one workflow with clear sources, such as HCP email variants or disease-awareness pages.
Load approved sources and rules first, before any drafting.
Route every output through your normal MLR process.
Measure review cycle time and first-round pass rate before and after.
Decide build, buy or partner for the next workflow based on what you learned.
Frequently Asked Questions
What is a custom AI agency for pharma?
It is a firm that designs and builds AI tools around a pharma company's own workflows, data and compliance rules, such as drafting from approved claims, generating variants or pre-checking content before MLR review. You then run or retain the agency to maintain what it built.
Should pharma companies build AI in-house or use an agency?
Build in-house when AI is strategic and you have engineers to maintain it. Use an agency for a unique workflow and a defined project. Use a platform when the work is common across marketing and you want approvals, audit and security built in.
What should a pharma AI build include?
Drafting from approved sources only, banned claims and mandatory statements enforced as rules, a hand-off into your MLR process, a person approving anything that goes out, an audit trail, enterprise security and a BAA where health data is involved.
Can Nagent build custom AI agents for pharma?
Yes, on its platform. Your team can build an agent from one sentence in Agent Workbench, and the Enterprise plan includes custom agents, workflows and integrations, with Nagent AI Labs engineers building alongside your team. Nagent is not an agency or an MLR system.
Choose the partner you can still run in a year
A custom AI build for pharma succeeds when it uses approved sources, respects MLR, records every decision and stays maintainable after launch. If a platform with custom agents fits your team better than a one-off build, see how Nagent works for pharma.
Book a demo to talk through your pharma use case.