Presses, coaters, granulators, blenders
Ship Pildeon-ready connectors and validated autonomy on the machine. The OEM's design space becomes the agent's wall.
Partners
Autonomy arrives through the people the plant already trusts.
Equipment OEMs for blending, granulation, compression and coating, PAT and NIR vendors, pharma MES vendors, and integrators and validation consultancies. The distribution moat Pildeon is building is a channel where the press, the coater and the probe ship Pildeon-ready.
Scenario: Run one immediate-release tablet batch through granulation, compression, coating and inspection inside the approved design space, with QA approval before release. A design walkthrough, not a customer record.
Programme
Four kinds of partner
Each brings something the plant already relies on.
Probes and analysers
Spectra become release evidence. The vendor's method validation is what Spectryn's evidence chain cites.
Systems of record
Genealogy and release packages written back into the system QA already uses. No parallel record.
Deployment and CSV
Deploy the edge node, map tags, run shadow mode and own the site validation package alongside the plant.
Commercial
How the partnership works
Simple, and written down.
Partners get
- Early access to the SDK, connectors and the twin harness
- Joint design-partner engagements and shared validation artefacts
- Referral and resale terms agreed per partner type
- A named engineering contact and a shared release line
Partners commit to
- Read-path documentation for their equipment or system
- Respecting the autonomy model: no write path without site QA
- Honest status: no shipped-feature claims for planned work
- Tenant isolation of plant data they help connect
Run timeline · scenario
What a partner-delivered run looks like
The press connector from the OEM, the spectra from the PAT vendor, the genealogy into the MES, the validation package from the integrator. Same run, four partners.
run_b2c7e1
Line 2 · rotary tablet press · scenario
SUCCEEDED
-
01
ingest.batch_record
SUCCEEDED
1.2 s
Plant Orchestrator · Pulled the master batch record, the approved design-space limits for this formulation and tooling family, and the site autonomy policy from MES; locked the target envelope for the run.
-
02
twin.rehearse
SUCCEEDED
41 s
Plant Orchestrator · Twindra simulated 36 candidate setpoint vectors on the as-made batch twin (granulation DEM, compression and ejection risk, coating CFD, dissolution surrogate) and ranked them on predicted content uniformity, capping risk and takt.
-
03
blend.uniformity
SUCCEEDED
6 m 10 s
Blend-and-Dispense · Spectryn scored in-line NIR spectra against the formulation's chemometric model; the blend reached its uniformity end point with confidence bounds inside the site acceptance limit and blending stopped on evidence rather than on a fixed time.
-
04
granulate.dry
SUCCEEDED
3 m 48 s
Granulate-and-Dry · Inlet air temperature and drying airflow trimmed inside the approved window to bring loss-on-drying to the target moisture band for compression; the move was bounded, logged and inside the design space.
-
05
compress.press
SUCCEEDED
2 m 02 s
Compress-and-Fill · Main compression force and feed-frame speed adjusted inside the approved window to hold tablet weight and hardness on target while the twin's capping-risk estimate stayed under the site threshold.
-
06
coat.spray
SUCCEEDED
4 m 25 s
Coat-and-Dry · Spray rate and inlet temperature re-phased against bed temperature and exhaust humidity to hold the film-coat window and avoid twinning and mottling; no excursion from the validated recipe envelope.
-
07
inspect.tablets
SUCCEEDED
continuous
Defect-and-Inspect · Visqa classified chips, cracks, capping, spots, mottling and print defects on six synchronised cameras, within the sub-100 ms design budget, and linked a rising chip rate to coating spray rather than to tooling.
-
08
spectra.release_evidence
SUCCEEDED
38 s
Quality-and-Potency · Spectryn assembled the method-linked evidence chain for content uniformity and moisture with confidence bounds and citations to the validated analytical method, ready for QA review.
-
09
approve.qa
APPROVAL
3 m 14 s
Plant Orchestrator · Batch release is above every autonomy level Pildeon offers. The package was held for the named QA reviewer, who approved it in the review console; the decision, the reviewer identity and the timestamp are in the Part 11 audit trail.
-
10
release.genealogy
SUCCEEDED
52 s
Quality-and-Conformance · Conforma wrote the time-aligned batch genealogy (every sensor state, recommendation, approved action, equipment response and QC result) and the cited release package to the immutable audit trail.
Onboarding
Becoming a certified partner
Three steps.
- Technical. Read-path connector built and validated against the partner's system in the twin harness.
- Joint engagement. One design-partner plant delivered together, shadow to assist.
- Certification. Write-path connector validated with site QA; partner listed on the integrations page.
Accelerated computing
Physical AI, at the press
Tablets leave a rotary press by the hundreds of thousands an hour. Perception has to be local, deterministic and fast, so Pildeon runs GPU inference on the plant edge and keeps training, simulation and optimisation on DGX, HGX or OVX, on-prem where the data cannot leave the plant.
Edge perception
Multi-camera chip, crack, spot and print inspection and NIR and PAT fusion on the plant edge. Design targets: under 100 ms per camera frame group, under 500 ms for a fused risk score.
Validated model serving
Vision, spectral, time-series and process-reasoning models behind one orchestrator, versioned, tenant-isolated, with bounded actions and audit schemas enforced at the serving layer.
Training and fine-tuning
Defect vision, coating appearance, NIR and PAT chemometrics, press and coater time-series models and process-window models, trained under GxP change control.
As-made batch twin
GPU-accelerated DEM granulation, CFD coating spray and drying, compression and ejection risk and a dissolution surrogate. Design target: nightly design-space sweeps per formulation family.
Synthetic rare faults
Capping, lamination, sticking, mottling, segregation and print-defect scenarios generated for class balance, always labelled synthetic and evaluated apart from real GMP evidence.
Optimisation and handling
Campaign and changeover sequencing, drying and coating energy allocation and line balancing with cuOpt; sim-first IBC and tooling handling policies trained and rehearsed with Isaac.
Fit
Who this works for
And who it does not.
Vendors with an OPC UA or API read path
If your equipment or system exposes its telemetry, the connector is weeks, not quarters.
Consultancies that own CSV
If you already write validation packages for OSD plants, you are the natural owner of the Pildeon site package.
Resellers without engineering
Pildeon is deployed, validated and supervised. A partner has to be able to do at least one of those.
Integrations
It speaks tablet plant, not cloud
Pildeon reads and writes through the systems already on the floor: presses, coaters, granulators, PAT probes, MES, LIMS and historians. No rip-and-replace, no parallel historian. Connectors are built with design partners against their stacks; the vendors listed are the ones common in OSD plants.
GEA, Glatt, Syntegon, Freund-Vector, L.B. Bohle
Blender, granulator and fluid-bed telemetry; bounded setpoint writes
Fette Compacting, Korsch, IMA, Syntegon, MG2
Force curves, fill depth, ejection force; bounded setpoint writes
GEA, Glatt, O'Hara, Thomas, Freund
Spray, inlet, bed temperature, exhaust humidity; bounded writes
Bruker, Sartorius, Viavi probes and analysers
Spectra across blend, granulation, drying and compression
Line cameras and existing inspection systems
Frames, defect maps, reviewed images
Körber Werum PAS-X, Rockwell, Siemens Opcenter
Master batch records, campaigns, batch genealogy
Site LIMS, OSIsoft PI and equivalent historians
QC results, time-series backfill and replay
Azure AD, Okta, LDAP · NVIDIA Jetson and on-prem GPU
SSO, RBAC, named approvers · inference at the line
Guardrails
An agent that can move a compression force needs a leash
Pildeon writes to production equipment in a GMP plant. Every capability is scoped to the approved design space, every write is policy-checked, every action is written to an immutable Part 11 audit trail the site owns, and no agent can release a batch.
- Bounded action space. Each agent can only write to an explicit setpoint allow-list, inside the limits the site's validation approved.
- Policy engine before every write. Autonomy level, design-space limits, batch state, model version and reviewer assignment are all evaluated before a setpoint moves.
- Human-in-the-loop gates. Batch release, any move outside the design space and any change to a validated parameter wait for a named QA reviewer.
- Immutable audit trail. Append-only, hash-chained, exportable, retained on the site's own storage, with reviewer identity and timestamp on every decision.
- Hard fallback. Loss of the edge node, the network or the model returns the line to the equipment's last known-good recipe.
- Tenant and IP isolation. Formulations, recipes and models never cross a customer boundary. Validated on-prem deployment is available for regulated producers.
Compliance posture
| Standard | Scope | Status |
|---|---|---|
| 21 CFR Part 11 | Audit trail, e-signatures, records | RUNNING Designed in from day one |
| GAMP 5 | Validation package for the platform | RUNNING In progress, planned for the first design partners |
| cGMP · ICH Q8 to Q13 | Design space, QbD, continuous manufacturing | RUNNING Design-aligned; site validation decides |
| SOC 2 Type I | Cloud control plane | QUEUED Planned, first six months |
| SOC 2 Type II | Cloud control plane | QUEUED Planned, months six to twelve |
| Data residency | Validated on-prem, air-gapped option | SUCCEEDED Available by design |
The first meeting
What each stakeholder asks first
Pildeon has no customer quotes to show yet, and will not invent any. These are the questions the three buyers in an OSD plant ask in the first meeting, and the answer each gets.
"What does this do to my reject rate, my deviation count and my release time, and how will you prove it on my line rather than on a slide?"
Site or manufacturing director · economic buyerAnswer: shadow mode first, baseline captured before any autonomous action, a written ROI target before a paid pilot.
"Will it ever move a setpoint outside the design space we validated, and can I see why it recommended every move it made?"
Formulation or process engineer (MSAT) · championAnswer: no, by construction. Every recommendation carries its reasoning trace and its citation.
"Where is the Part 11 audit trail, who signs the release, and what happens to my validated state when the model changes?"
QA, quality and compliance lead · approverAnswer: an immutable audit spine, a named QA reviewer on every release, and every model change under GxP change control.
Enterprise
Standardise validated autonomy across the group
One policy model, one audit spine, one benchmark across every line in every plant, with formulation and tooling models kept private to each site.
- SSO, RBAC and named approvers down to the setpoint level
- Group autonomy policy with per-site override and approval chains
- Cross-plant benchmarking on yield, rejects, deviations and energy
- Validated on-prem and air-gapped plant-edge deployment options
- Validation packages and change-control records as first-class deliverables
- Dedicated deployment engineer and quarterly model review per site
FAQ
Straight answers
The questions site directors, MSAT engineers and QA leads actually ask in the first meeting.
Yes, but only inside an explicit setpoint allow-list bounded by the design space your validation approved, and only at the autonomy level your site has set. Level 0 is shadow mode: Pildeon observes and predicts and writes nothing. Most sites spend their first weeks there.
No. The approved design space is a wall the policy engine enforces at call time. A move outside it, or a change to a validated parameter, is a change-control event that waits for QA sign-off. No autonomy level removes that gate.
A named QA reviewer, every time. Pildeon assembles the evidence chain and the cited release package; the reviewer approves or rejects it in the review console, and the decision, identity and timestamp land in the Part 11 audit trail.
The line returns to the equipment's own last known-good recipe. Pildeon is a supervisory layer on top of your existing control systems, never a replacement, so an outage degrades the line to the way it runs today, not to a stop.
Only if you choose cloud training. Formulations, recipes, spectra and defect libraries are tenant-isolated and never used to train another customer's models. Validated on-prem deployment with an air-gapped plant edge is available.
Shadow mode on one wedge workflow first, with baseline rejects, deviations, yield, energy and release time captured before any autonomous action. Assist mode once prediction accuracy is shown against QC results. A paid validated pilot only when there is a written ROI target. Timelines depend on the site's validation and change-control calendar.
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