One platform. Every workflow, from evidence to decision.
AI software for life sciences organisations and specialist consultancies, built to hold your evidence, apply your methods and run as part of how your team works every day.
What you actually receive.
- The software your team uses
- The admin tools to run it
- Your evidence and knowledge, in one place
- Your way of deciding, built in
- AI that stays on your material
- Everything needed to run it safely
Delivered as capability your team owns.
Your most valuable capability
probably is not written down.
It lives across experienced people, inherited processes, presentation decks, spreadsheets, shared drives and agency relationships. That creates a familiar pattern.
The work gets completed, but the reasoning disappears. A decision gets made, but nobody can reconstruct why. A methodology creates value, but only when the right senior person is in the room. Evidence is collected again and again because no trusted system retains it.
VISFO Product turns that fragmented capability into software your organisation can use, govern and improve.
Software your organisation actually runs on, not another dashboard or another AI trial.
One connected system, built around your work.
Every VISFO product contains four essential parts. The interfaces will change over time. Your organisational knowledge should endure.
- 01 / 04
What your organisation knows
Your evidence, your terminology and the context the software needs to understand your world. Everything linked to its source, versioned and controlled, so the system has a reliable memory your team can trust.
- 02 / 04
How your teams work
The screens people use to do the actual job: reviewing evidence, building strategies, approving work, preparing deliverables, tracking stakeholders. Each one draws on the same information and adds back to it. It is live, not something people check in on: people are notified the moment something needs them, and colleagues can pick up the same piece of work together rather than emailing versions back and forth.
- 03 / 04
How decisions get made
The scoring and rules that help teams compare options and choose. Every recommendation comes with the evidence and reasoning behind it, so people can check it rather than take it on trust.
- 04 / 04
How it gets better
Testing, quality checks, user feedback and release records that show whether the software is getting more reliable, so improvement is something you can point at.
Software your team owns and runs.
Depending on what you need, an engagement can include all of the following.
The software your team uses
Built around the roles, tasks and decisions your people actually have. Always on: notifications when something needs attention, and shared views so people are working together on the same thing, not comparing versions afterwards.
The admin tools to run it
Permissions, content updates, approval steps and reporting, so your team can manage it without calling us.
Your evidence and knowledge, in one place
Your evidence, terminology and relationships, structured and linked back to their sources.
Your way of deciding, built in
Your scoring, methods and prioritisation rules, written into the software so everyone applies them the same way.
AI that stays on your material
AI that works from your approved knowledge, inside tasks our domain experts have written and checked, not an open chat box that can say anything.
Everything needed to run it safely
Log-ins, audit trails, connections to your other systems, hosting, monitoring and updates, built for environments where 21 CFR Part 11, GxP and SOC2 are the minimum bar.
Delivered as lasting organisational capability, not a prototype handed over after a demonstration.
“We design products that earn their place in the daily routine, not demos that gather dust after the pilot.”
That's what we build. Here's how.
Start with the work. Then build the software.
We start with the decisions your team makes, the way the work moves and the knowledge you cannot afford to lose. The features follow from that.
Agree what it has to do
We work out who uses it, what decisions it supports, what evidence it needs and how we will know it is working. You get a clear picture of the software before anyone designs a screen. This is the step most AI-generated prototypes skip, which is exactly why they can't be extended into something your team relies on.
Build the first version
Log-ins, permissions, your knowledge base and the first part of the job are set up, and a small group starts using it.
Put real work through it
We build out the rest using your actual projects, evidence and people. The software starts producing real deliverables and supporting live decisions.
Add to it and improve it
New parts of the job get added based on how people are actually using it, and every release is checked for quality and reliability.
- Weeks 1–2
Agree what it has to do
We work out who uses it, what decisions it supports, what evidence it needs and how we will know it is working. You get a clear picture of the software before anyone designs a screen. This is the step most AI-generated prototypes skip, which is exactly why they can't be extended into something your team relies on.
- Weeks 3–6
Build the first version
Log-ins, permissions, your knowledge base and the first part of the job are set up, and a small group starts using it.
- Weeks 7–12
Put real work through it
We build out the rest using your actual projects, evidence and people. The software starts producing real deliverables and supporting live decisions.
- Weeks 12+
Add to it and improve it
New parts of the job get added based on how people are actually using it, and every release is checked for quality and reliability.
Pilot. Build. Operate.
Prove it on one piece of work, build the full system, or keep extending it alongside your team.
Pilot
Start with one team, one decision or one thing you do repeatedly. The point is to put real work through it and see whether it holds up.
Typically 4 to 6 weeks
- The first version of your knowledge base
- One working part of the job, end to end
- Software your team can use
- An agreed measure of whether it is working
- Feedback from the first users
Build
Build the real system around the work, evidence and decisions your organisation needs it to support.
Typically 3 to 6 months
- The live software
- Admin tools for your team
- Permissions and a record of who did what
- Your evidence and knowledge, in one place
- The main parts of the job covered
- The first decision support built in
- Hosting and monitoring
Operate
We work alongside your product owner and experts to look after the system and keep adding to it.
Ongoing, quarterly
- New features and workflows
- Keeping the knowledge current
- Upgrades as AI models improve
- Quality checks
- Performance monitoring
- Regular releases against an agreed plan
Two reasons organisations build with us.
Turn the expertise you already have into software, or give your team one place to work instead of a dozen disconnected tools.
Turn your expertise into software.
Your method is the valuable part. If it can only be delivered by senior people on bespoke projects, growth stays tied to the hours they have.
Your frameworks become steps in the software.
Your scoring becomes something the software applies.
The knowledge you have built up becomes reusable.
Your clients get something they can log into, not another deck to file. You keep your brand, you keep your IP, and you decide how it is sold.
- More value delivered without adding the same number of people
- Recurring product revenue alongside services
- More consistency across teams and clients
- Your senior expertise applied on every engagement
- Client relationships that carry on between projects
Give the team one place to work.
In most teams the evidence sits in one place, the plans in another, and the decisions in meeting notes. Agencies hold part of the history, and AI tools get bolted on without the context to be useful.
Evidence is captured once.
Decisions stay attached to the reasoning behind them.
Deliverables stay linked to their sources.
We build one place the work runs through, so everyone is working from the same version.
- One place your team trusts for evidence and knowledge
- Less repeated research and duplicated agency work
- Decisions that stay visible and easy to review
- Software shaped around how the team actually works
- AI that works from your approved knowledge
How we build.
Four things you can expect from every product we build with you.
- 01
Built to be used every day
We do not judge it on whether the demo impresses people. We judge it on whether your team still relies on it six months later.
- 02
Built around your expertise
We do not turn up with a generic platform and ask you to fit around it. We build around your evidence, your terminology, your methods and your decisions.
- 03
You can always see where something came from
Evidence, recommendations, approvals and deliverables stay connected, so a decision can be explained long after the meeting where it was made.
- 04
The AI model is not the valuable part
Models keep changing. What lasts is your knowledge, your decision rules, your workflows and the way quality is tested. Every task the AI performs runs on instructions written by someone who has worked in your domain, and checked by someone else who has too, and every model change is tested against a baseline before it reaches your team. That is what your organisation owns.
Projects answer a question.
Products change how the question is answered.
A VISFO Project delivers a defined answer and the interactive views that support it. A VISFO Product embeds the evidence, workflows and decision process into software your organisation operates over time.
Many organisations begin with a project. Product becomes the right choice when the process is valuable enough to repeat, govern and bring in-house.
What teams ask us first.
01How is this different from your projects offering?
02Do we own the software at the end?
03How do you handle compliance, audit and validation?
04Can we start small?
05Do you build us a custom AI model?
Two more ways we help.
Cross-functional, medical affairs, market access, HEOR.
These are examples of systems we can build with you, not off-the-shelf products to buy. Filter to see what each involves, then add the pieces you'd want to your scope and send it over.
Built from real work, not a fixed catalogue.
Everything below is a capability we've already built for a team like yours, evidence review, payer modelling, medical information, and more. It's a starting point for the conversation, not the limit of it. We're a software team first: we sit down with your experts, learn how your team actually works, and build around that. Every capability, whether it's one of these or something new, is governed and reviewed the same way.
Evidence Synthesis Engine
TLRs, meta-analyses and living evidence. The inputs every other surface trusts.
The central surface. Runs targeted literature reviews, meta-analyses and living evidence pipelines, with structured outputs that feed TPP Builder, Narrative Workbench, NMA/ITC, Model Studio, Burden Engine, GVD and HTA Console. One canonical evidence base, kept current.
TPP Builder
One living TPP the whole team works inside.
A collaborative cross-functional workspace where the TPP stays evidence-anchored as new data lands. Medical, commercial, access and HEOR work the same artefact; versions, claim sources and trade-offs are tracked automatically; downstream assets pull from the same spine. Powered by the Evidence Synthesis Engine.
Narrative Workbench
One claim hierarchy every asset draws from.
The shared scientific spine for an asset, made workable. Core, pillar and supporting claims tiered and tagged by audience, each claim anchored live to its evidence object from the Evidence Synthesis Engine. Medical slide decks, payer dossiers, congress communications and field tools all pull from the same approved hierarchy, with audience-specific framing layered on top.
Stakeholder Graph
A live graph of the people who move your TA, and who moves them.
Continuously identifies, scores and re-ranks payers, KOLs, investigators, societies and advocates as a single graph, with engagement history, publication and guideline signal, and influence weighting kept current. The shared people-layer that medical, access and commercial all read from.
Advocacy Graph
The long-view advocacy relationships, kept warm.
A relationship graph across patient advocacy organisations: who you're engaged with, what you've offered, what's overdue, and where the next partnership should land.
Signal Watch
Always-on tracking of the events that actually move your numbers.
Watches competitors, regulators, payers, guideline bodies and congresses on a curated watchlist for your asset, filters the noise, classifies what changed, scores impact on forecast, dossier and narrative, and routes the next action.
Regulatory Intelligence Hub
Agency precedent, label tracker, submission watch, across FDA, EMA, PMDA and beyond.
A standing view of regulatory precedent, label evolution and submission activity across major agencies, wired into Signal Watch and the HTA Console so regulatory and access stay in step.
Forecasting Studio
Demand, patient-flow and scenario forecasts in one place.
Builds and stress-tests forecasts, epidemiology, treatment pathways, uptake scenarios, joined up to Patient Journey Studio, Burden Engine and Reimbursement Strategy Console.
Patient Journey Studio
Map patient and treatment pathways from real-world data.
Builds patient journeys and treatment pathways from claims, EHR and registry data, touchpoints, drop-offs and switch points, ready to read across medical, access and commercial.
Asset Decision Hub
Early-asset portfolio, TPP variants and Go/No-Go gates in one place.
A decision surface for early assets, portfolio view, development scenarios, TPP variants, Go/No-Go evidence packages and investment cases tracked through every gate.
Partner Evaluation Workbench
BD and alliance partner evaluation with traceable evidence.
Structured profiling, scientific signal, execution capability, strategic fit and risk concentration for every partner candidate, with audit-grade rationale behind every recommendation.
Omnichannel NBA Engine
Next best action across every stakeholder touchpoint.
An orchestration layer that recommends the next best action, sequences it across channels, and measures response, joined up to the stakeholder map and engagement history.
Engagement OS
Plan, log and measure every scientific interaction in one place.
A workflow layer for medical, MSL and access teams to plan engagements, log interactions, and roll up coverage and sentiment across the stakeholder map.
Field Medical Excellence
Personalised listening imperatives per HCP, scored notes, strategy that learns.
An operating system for field medical: strategy-driven listening imperatives per HCP, scored MSL notes, and a closed feedback loop that sharpens the next visit, not just reports on the last one.
Field Insights Engine
Structured capture and synthesis of every MSL and medical interaction.
Turns unstructured field interactions into structured insight, themes, objections, unmet needs, synthesised across the team rather than buried in a CRM.
Advisory Board Studio
Design, run and capture advisory boards without losing the insight.
End-to-end ad board workspace: agenda design, expert prep, live capture, structured synthesis, with outputs flowing into Field Insights, TPP Builder and the Narrative Workbench.
Medical Information Hub
Med info queries, standard responses and the signal hidden in them.
A managed med info workspace, query intake, standard response library, fulfilment tracking, plus the analytics layer that turns query patterns into medical strategy signal.
Publication & Congress Planner
Publication plan and congress strategy on one timeline.
Plans manuscripts, abstracts and congress sessions against the narrative spine, flags gaps, and tracks impact, so the next 18 months of scientific output is choreographed, not improvised.
MSL Performance Console
Insight quality, coaching cues and territory analytics in one view.
A performance layer for field medical, insight quality (Insight Score), coaching cues per MSL, territory coverage and KPI roll-ups, all joined up to engagement data and field insight themes.
Medical Impact Dashboard
Measure scientific exchange, narrative penetration and KOL adoption.
A standing measurement layer for medical affairs, share of voice, narrative penetration in the literature, KOL adoption of key claims, joined up across the stakeholder map.
GVD Workbench
A modular GVD affiliates actually localise.
A platform for assembling, updating and localising the global value dossier as a set of reusable modules, not a 400-page PDF that goes stale on day one. Each module reads its claims and evidence live from the Evidence Synthesis Engine, NMA / ITC Engine and TPP Builder, so every affiliate dossier stays consistent with the global story.
HTA Console
An agency-tuned cockpit for NICE, HAS, G-BA and beyond.
Submission templates, review cycles and evidence packs tuned to each agency's expectations, with the GVD modules, NMA estimates and economic models wired in. One asset, many agencies, one provenance trail. Powered by the Evidence Synthesis Engine.
Payer Value Composer
Sharp value story, objection bank, archetype-tested.
The working surface for the payer value story. Claims, evidence anchors, anticipated objections and pre-tested rebuttals by payer archetype, kept in lockstep with the GVD, NMA / ITC Engine and Model Studio. The story the field actually carries into the room.
Reimbursement Strategy Console
Payer-by-payer strategy, success likelihood, decisions tracked.
A standing view of your reimbursement strategy, payer-by-payer plan, likelihood scoring, decision history and what to do next, joined up to the value story and HTA submissions.
Pricing Corridor Studio
Reference-pricing exposure, scenario corridors and launch sequence in one room.
Models international reference pricing exposure, parallel-trade risk and launch sequence trade-offs, every corridor decision recorded with the assumptions, precedent and ceiling that justify it.
Country Launch Sequencer
Sequence launches by HTA readiness, pricing risk and reference effects.
Plans launch order across markets, HTA readiness, reference pricing knock-on effects, payer appetite, so the global sequence optimises revenue rather than reacts to deadlines.
Model Studio
CE and budget-impact models built once, defended everywhere.
A hosted modelling environment for cost-effectiveness and budget-impact models, transparent assumptions, country-ready inputs, version history, reviewer-friendly outputs and live wiring to the NMA Engine, GVD Workbench and HTA Console.
Value Engine
The payer-facing front door to the CE and BIM core. A live calculator with audit trail, not a PDF.
The payer-facing surface of Model Studio. A configurable, in-room calculator that turns the canonical CE and BIM into a scenario conversation, local inputs, plain-language outputs, every run logged with its assumption set and a leave-behind generated on the spot.
Evidence Gap Console
Standing view of what's missing and what to commission next.
Maps the evidence you have against what payers and HTA agencies demand, scores the gaps and ranks the studies that will move decisions, refreshed every time the evidence base, the model or the dossier moves.
RWE Console
Your RWE roadmap, kept aligned to the questions decision-makers ask.
Keeps the RWE roadmap aligned with the decisions it has to support, data partnerships, study design, feasibility and read-out cadence tracked in one view, with every study tied back to the gap it closes.
Burden Engine
A standing burden-of-illness dataset that stays current.
A managed BOI dataset for your indication, epidemiology, cost, quality-of-life and productivity evidence, refreshed on a cadence so the unmet-need argument never goes stale. One canonical dataset that the Model Studio, GVD, HTA Console and advocacy work all read from.
NMA / ITC Engine
Network meta-analysis and MAIC / STC, submission-grade, fully traced.
Builds the trial network live from the Evidence Synthesis Engine, runs network meta-analysis and indirect treatment comparisons (anchored, unanchored, MAIC, STC) and produces reviewer-ready outputs with full provenance back to each trial. Feeds Model Studio, GVD and the HTA Console.
QoL & PRO Studio
Utility derivation and PRO analysis, payer-ready.
A working environment for QoL and patient-reported outcomes, utility mapping, PRO analysis, instrument selection, feeding the economic models with consistent inputs.
DCE & Preference Studio
Discrete choice experiments and preference elicitation, end to end.
Design and run discrete choice experiments and preference studies, instrument design, fielding, analysis, with outputs that drop straight into the value story and economic models.
Build what comes next.
Whether you need growth, answers or capability, VISFO helps you move earlier and faster.