Real scenario walkthrough

From ingredient selection to production blueprint in 6 steps

Follow a real formulation scenario: a broiler gut health blend using oregano and thyme oils. See exactly what PhytoForm AI does at each stage — and what it replaces.

The scenario

A mid-sized feed additive company needs to develop a broiler gut health blend using oregano essential oil (80% carvacrol chemotype), thyme oil, and a silicon dioxide carrier at 150 ppm in complete feed — validated for EU and US markets.

~6 credits
Total cost for this workflow
1

Define your target

Normally: hours researching which analytes matter for your target species and health domain

What you do

You’re developing a broiler gut health blend targeting improved intestinal integrity and reduced pathogen load. You select "Poultry" as the species and "Gut Health" as the primary domain.

What PhytoForm AI does

The formulation engine loads domain-specific parameters: target analytes for gut health (carvacrol, thymol, cinnamaldehyde), recommended inclusion rates for broilers, and the regulatory constraints for your selected markets.

Output: Domain-configured workspace ready for ingredient selection

2

Select ingredients and generate the formulation

1 credit

Normally: days of mass-balance spreadsheets and literature cross-referencing

What you do

You add oregano essential oil (80% carvacrol chemotype), thyme oil, and a silicon dioxide carrier. You set the target inclusion rate at 150 ppm in complete feed.

What PhytoForm AI does

The engine calculates the projected analyte profile based on ingredient assay values, inclusion rates, and known interactions. It accounts for carrier dilution and active compound ratios.

Output: Formulation version with full ingredient breakdown and projected analyte concentrations

3

Review the COA specification

1 credit

Normally: weeks waiting for lab results before you know if your blend hits spec

What you do

You generate a Certificate of Analysis specification. The system projects that your blend will contain 45.2 ppm carvacrol with a confidence band of ±15%, giving you a min/max range of 38.4–52.0 ppm.

What PhytoForm AI does

The COA engine uses mass-balance calculations combined with calibration data from previous lab results (if available) to project each analyte. Confidence bands are adjustable and reflect real-world production variance.

Output: Downloadable COA spec with projected analytes, ranges, and band widths

4

Scan your marketing claims

1 credit

Normally: $300+/hr regulatory consultants, weeks of back-and-forth per market

What you do

Your marketing team wants to use the claim: "Prevents E. coli infection in broilers." You paste it into the risk scanner and select EU + US as target markets.

What PhytoForm AI does

The scanner flags this as HIGH RISK for both markets. In the EU, therapeutic claims for feed additives require veterinary medicinal product authorization. In the US, structure/function claims are permitted but disease claims are not for feed additives.

Output: Risk flag with explanation + suggested alternative: "Supports intestinal microflora balance" (compliant in both markets)

5

Generate the manufacturing blueprint

2 credits

Normally: production team assembles instructions manually, CCPs often missed

What you do

You generate a manufacturing blueprint for a 500 kg batch. The system produces step-by-step production instructions.

What PhytoForm AI does

The blueprint includes mixing sequences, temperature parameters, granulation steps if applicable, and flags Critical Control Points (CCPs) — for example, ensuring essential oil addition occurs below 40°C to prevent volatile loss.

Output: Step-by-step blueprint with CCP flags, QC checks, and equipment notes

6

Close the loop with lab data

Free

Normally: manual comparison in spreadsheets, no system-wide learning

What you do

Your production batch comes back from the lab. Carvacrol measured at 42.8 ppm — within your projected range of 38.4–52.0 ppm. You upload the lab result.

What PhytoForm AI does

The system calculates deviation (−5.3% from projected) and confirms the result is within the confidence band. This data point is stored and used to calibrate future projections, improving accuracy over time.

Output: Deviation report with projected vs. actual comparison and band compliance status

End result: a production-ready, regulation-checked formulation

In the time it takes to set up one meeting with a regulatory consultant, you've completed the full workflow.

Formulation with projected COA

Regulatory claim scan for 2 markets

Manufacturing blueprint with CCPs

Lab calibration for future accuracy

Beyond the walkthrough

The scenario above covers one formulation workflow. Here's what else PhytoForm AI handles.

13 document types

Technical data sheets, safety summaries, efficacy trial templates, product specs, and more — each structured to your target market’s requirements.

Dossier compiler

Assemble complete EU Technical Dossiers, US GRAS Notices, or Brazil MAPA filings with section tracking and completeness scoring.

Authorization roadmaps

Visualize the full path to market authorization with timelines, dependencies, and cross-market mutual recognition advice.

Multi-market regulatory checks

Check ingredient status, contaminant limits, and registration requirements across 8+ markets in a single lookup.

Version history

Every formulation change creates a new version. Full audit trail of ingredients, analytes, COA specs, and lab results.

Team collaboration

Invite formulators, regulatory affairs, and QA team members. Shared workspace with role-based access.

Try it with your own formulation

The scenario above used ~6 credits. Free accounts include starter credits — enough to run your first formulation end-to-end. No credit card required.