Enterprise story intelligence
Story intelligence built around your organization.
Scripitt gives production companies, agencies, studios, publishers and content enterprises a private story-intelligence environment for evaluating, comparing, developing and routing scripts, manuscripts and IP.
Enterprise engagements are configured around your team, workflow, content volume and deployment requirements.
Who we build for
Configuration, not tiers. What an engagement includes depends on the organization, the workflow and the volume it has to carry.
Production Companies
For independent studios, production companies, development teams and talent-led content companies.
Capabilities can include
- Multi-format story evaluation
- Evaluation LensPatent pending
- Alignment RadarPatent pending
- Decision Briefs and recorded company decisionsPatent pending
- Library and revision intelligencePatent pending
- Branded reports and workspacePatent pending
- Team access
Agencies, Management & Publishers
For organizations evaluating and routing high volumes of scripts, manuscripts, submissions and underlying IP.
Capabilities can include
- High-volume intake and evaluation
- Portfolio and library intelligencePatent pending
- Side-by-side project comparison
- Custom organizational lensesPatent pending
- Buyer and market alignmentPatent pending
- Provenance and revision trackingPatent pending
- Team workflows and branded outputsPatent pending
- Library registers for export and print
Studios & Enterprise Platforms
For major studios, streamers, publishers and large content organizations requiring institutional story-intelligence infrastructure.
Capabilities can include
- Organization-wide story intelligence
- Custom evaluation frameworksPatent pending
- High-volume processing
- Multi-team workflows
- Enterprise governance and usage controlsPatent pending
- White-label workspace, shares and exportsPatent pending
- Your own AI credentials, isolated per workspacePatent pending
- Deployment planning and enterprise support
Patent pending marks capabilities covered by pending United States patent applications held by HAAIS Inc.
What is actually running
An engine, not a chatbot.
Scripitt is a story-intelligence system. A language model is one component inside it, called at defined steps to read and assess. Everything around those steps is Scripitt's own engineering, and none of it can be talked into a different answer.
Change the model and the platform keeps working. Remove the platform and the model is just a prompt.
Intake and structure
Eight formats, scanned pages, size-aware routing and a complete comprehension pass that structures the whole work before any judgment is formed.
Orchestration
Mode-specific specialist reads run in parallel against the lens you chose, then a reconciliation step resolves their disagreements instead of averaging them away.
Validation
Every output passes a bounded validation ladder that rejects, repairs and re-checks weak work. A report that cannot clear it says so rather than inventing confidence.
Scoring and verdict
Weighted scorecards, strategic scores and the Pass / Consider / Recommend verdict are computed by the system from the evidence, not improvised in prose.
Memory and provenance
Fingerprints, an append-only chronology, same-text detection, revision-aware scoring and coverage numbers bound to the exact draft.
The human layer
The company decision is recorded as its own state, above the machine recommendation, with who, when, which draft and why.
AI credentials and model governance
Model-flexible by design.
Organizations can use Scripitt-managed AI infrastructure or, for eligible enterprise deployments, connect their own approved AI-provider credentials. Scripitt-managed workspaces run on a single approved provider and one tested model configuration; any additional provider is enabled for a workspace only at the organization's request. Provider selection, model access and fallback behavior are governed at the workspace level, while Scripitt's story-intelligence workflow, evaluation framework and decision infrastructure remain independent of any single model.
The model sits inside the machine. It isn't the machine.
Bring your own AI account
Run analysis through your organization's approved provider credentials, held in a vault, never shown again after saving, and never billed through Scripitt.
Provider isolation
Scripitt-managed workspaces are not rerouted to a second provider on failure unless your organization has asked for one. When you use your own AI account, your material is not rerouted through Scripitt's credentials — not on failure, not on fallback. Fallback happens only to a provider you have configured and connected yourself.
Model flexibility
Scripitt's intelligence workflow is separated from individual model versions. Every workspace runs the same tested configuration unless the platform administrator pins a different approved model for it, and approved models can evolve without rebuilding the platform.
Continuity
Provider and model selection are workspace-level settings. Because the evaluation framework and decision infrastructure are separated from any single provider, an approved provider can be changed without rebuilding the workflow.
The purchase
Not reports. An intelligence capability.
Traditional coverage evaluates one piece of material at a time. Scripitt gives an organization a persistent intelligence layer across its creative pipeline and library.
Evaluate
Scripts, pilots, pitches, treatments, manuscripts, adaptations, publishing material, vertical series and time-sensitive material through purpose-built professional modes.
Compare
Evaluate multiple projects side by side and surface decision-ready distinctions.
Route
Patent pendingUse Alignment Radar to identify natural market lanes, likely buyers and creative affinities.
Learn
Patent pendingBuild reusable custom lenses from an organization's own prior material and evaluation history.
Remember
Patent pendingMaintain persistent project history, provenance, revisions, reports and institutional knowledge.
Brand
Patent pendingDeliver the workspace, every shared report and brief, and every export within the organization's own visual identity — imported from its website in one step.
Enterprise decision architecture
Analysis, recommendation, decision, memory — one connected record.
Depth when you need to understand. Compression when you need to decide.
01
Analysis
What does the evidence say?
The full Story Intelligence Report — deep analysis, scoring, development, alignment, market, adaptation and risk intelligence, with citations back to the page. For the people who need the evidence.
See the evidence →02
Recommendation
What does Scripitt conclude?
The Executive Decision Brief — the recommendation, rationale, confidence, critical opportunity, material risk, alignment, next action and decision-changing factors, derived from the same record. For the person who has to make the call.
Make the call →03
Human decision
What did the organization actually decide?
The Company Decision — Recommend, Consider or Pass, by whom, on which draft, when, and why — recorded as its own state, separate from and above the machine recommendation.
04
Memory
What should the organization retain?
The library keeps the analysis, the recommendation, the human decision, the material history and every revision connected to one intelligence record, so the organization learns from its own reads over time.
Different roles. Different depth. Same underlying read.
A development team can work from the comprehensive analysis. An executive can make the call from the Decision Brief. Leadership can record the company decision. Scripitt keeps those layers connected to the same material and intelligence record.
Velocity
From reading backlog to decision velocity.
Scripitt compresses work that traditionally takes days into a structured story-intelligence workflow delivered in minutes, while keeping the human decision-maker in command.
AI reads.
Humans decide.
The evaluation is an input to a person’s judgment, with its reasoning exposed so a reader can disagree with it on the evidence.
Questions
Does Scripitt write or rewrite creative material?+
No. Scripitt does not generate creative material of any kind. It reads what is submitted and produces an assessment of it. The writing stays the writer's.
How long does an evaluation take?+
Minutes rather than days for a standard feature or pilot. Longer manuscripts take proportionally longer because the whole work is genuinely read before anything is judged. We position on speed, not on a contractual turnaround.
What happens to material submitted to the platform?+
It is stored against your organization's workspace under row-level access control, visible to your team and whoever you share it with. Scripitt does not use submitted scripts, manuscripts or other customer material to train Scripitt models. Scripitt-managed analysis runs on a single approved AI provider whose commercial terms do not permit training on customer inputs, and no second provider is used unless your organization asks for it. Projects can be deleted by their owner, and share links can be revoked at any time or set to expire. Enterprise organizations may also run Scripitt on their own approved AI-provider account, subject to the data-handling terms of that provider.
Is Scripitt just an AI wrapper?+
No. A general-purpose model handed a script produces an opinion. Scripitt produces a governed evaluation: a complete comprehension pass, parallel specialist analysis reconciled rather than averaged, a validation ladder that rejects and repairs weak output, weighted scoring, provenance, revision tracking and a recorded company decision above the machine's recommendation. The model does the reading at defined points inside that process. The process is the product, and it is what the pending patents cover.
See Scripitt on your own material.
Enterprise evaluations begin with a defined use case, representative material, workflow alignment and agreed success criteria.