Dedoctive
UK sovereign neuro-symbolic AI that grounds every answer in verified sources and shows exactly where it came from.
Dedoctive is worth a serious look if you are producing outputs that will be challenged — a risk assessment, an evidence review, a compliance sign-off. The differentiator is not the answer, it is the audit trail: provenance hyperlinks into verified sources (including table cells and image text), Response Maps, and an explicit refusal when no answer is available, all wrapped in BPMN workflows you design visually. The free Developer Edition IDE lets you test that before committing. It is a poor fit if you want a fast general assistant; for that, ChatGPT or Claude are the obvious picks, and for teams that mainly need document Q&A with citations, NotebookLM-style tools are lighter. Enterprise
Verified 3d ago · liveness 54/100 · cite: rightaichoice.com/tools/dedoctive
- Assurance and compliance officers who must defend an AI-assisted decision
- Public-sector policy and planning teams working from document-heavy sources
- Healthcare organisations reviewing sensitive evidence
- Supply chain and crisis response cells
- People who want fast, casual, unverified AI chat
- Teams with no document-heavy decision process to ground
- Deployments where on-premises or private-cloud options are impossible
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Skip Dedoctive if you want a general-purpose assistant that answers instantly from its own knowledge — Dedoctive only answers from sources you have verified and will tell you when it has no answer.
Building curated knowledge models and BPMN workflows takes expert configuration effort before the first defensible output appears.
Dedoctive sits at the enterprise/regulated end of the market rather than the per-seat productivity end. The free Developer Edition IDE and a free micro-pilot let a technical evaluator prove the provenance and workflow mechanics against one real decision process before any commercial commitment. Compare that with general assistants like ChatGPT or Claude, which cost far less per seat but offer no source-level audit trail, and with specialist document-Q&A tools that cite passages but stop short
In short
Dedoctive — UK sovereign neuro-symbolic AI that grounds every answer in verified sources and shows exactly where it came from. Best for Assurance and compliance officers who must defend an AI-assisted decision, Public-sector policy and planning teams working from document-heavy sources, Healthcare organisations reviewing sensitive evidence. Free to use.
What people actually say about Dedoctive — is it worth it?
We scanned public community sources for Dedoctive on Oct 18, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 2 of the posts we fetched could be positively tied to Dedoctive. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
Viability Score
How well maintained and how widely used is Dedoctive? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Curated knowledge models built from validated sources
- Granular provenance hyperlinks down to table cells or image text
- Human-in-the-loop governed workflows designed visually in BPMN
- Neuro-symbolic AI combining LLM reasoning with symbolic control
- Multi-format ingestion: documents, data, tables and images
- Response Maps showing how an answer was formed
- Explicit 'no answer available' response instead of a guess
- Interactive visuals for analysing arguments and exploring context
- Displays deep connections between apparently unrelated information items
- Professional-grade structured analysis using human best practices
- Free Developer Edition IDE for building and debugging workflows
- Agentic and deterministic processing combined in one workflow
- Open-standard compliant with no proprietary software dependencies
- Wraps any large language model without training
- On-premises / private cloud deployment
About Dedoctive
Dedoctive is a neuro-symbolic AI platform for organisations where a decision has to survive scrutiny. You feed it documents, data, tables and images; it builds curated knowledge models from those validated sources, then runs them through hybrid BPMN workflows that mix AI reasoning with deterministic, human-authored process steps. Every output carries granular provenance links — down to a single table cell or background text inside an image — and visual Response Maps show how the answer was assembled. If no source supports an answer, Dedoctive says so rather than inventing one. It wraps any large language model without training and is designed with no dependencies on proprietary software, and it ships a free Developer Edition IDE for building and debugging open-standard workflows combining agentic and deterministic processing. Domain packs include Safety Navigator, Crisis Navigator and Healthcare Navigator. Dedoctive is a UK sovereign technology developed with support from the MoD, Innovate UK and UK charitable funding, certified to Cyber Essentials, with on-premises/private-cloud deployment and an automated redaction mechanism for cases where nothing may be transmitted to cloud services. It is aimed at assurance, compliance, healthcare, supply chain and crisis response teams rather than casual AI chat.
Behind the Verdict
Most AI tools ask you to trust the output. Dedoctive is built on the opposite premise: the output is only useful if you can click through to the evidence and defend it. That shows up in three concrete mechanisms. Curated knowledge models constrain responses to validated information that meets the GOV.UK Data Quality Dimensions (correct, complete, consistent, current, concise, checkable). Granular provenance hyperlinks trace a statement back to a source — including individual table cells and background text in an image, which is where generic retrieval tools usually give up. And Response Maps visually show how the answer was formed, so a reviewer can interrogate the reasoning rather than accept it. What you are really buying is process control. Workflows are designed visually in BPMN, so AI reasoning sits inside a transparent, compliant process authored by human experts rather than inside a black box. Dedoctive describes the result as specialist multi-step workflows with human-in-the-loop guardrails, and it states plainly that it is unable to hallucinate because answers are drawn only from verified sources — and that it will say when no answer exists. That explicit 'no answer' behaviour is the single most underrated feature here: for compliance and healthcare work, an admitted gap is more valuable than a confident guess. The trade-offs are real. Building curated knowledge models and auditable agentic workflows is configuration work, not a five-minute signup, and value depends on the quality of the sources you curate. Because Dedoctive wraps any large language model, your answer quality also moves with whichever model you attach. The domain Navigators (Safety, Crisis, Healthcare) shorten the path for regulated settings, but they are the vendor's framing of the problem, not a substitute for your own evidence discipline. Where it fits: assurance and compliance functions, public-sector policy and planning teams, healthcare evidence review, supply chain and crisis response cells — anywhere a document-heavy decision has to be reconstructed later. Where it does not: casual chat, brainstorming, or any task where an unverified but plausible answer is good enough. For those, use a general assistant. The deployment options matter too: on-premises or private cloud, Cyber Essentials certification, and an automated redaction mechanism that prevents data being transmitted openly to cloud services, with UK sovereign status and MoD, Innovate UK and charitable backing behind it.
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Real-world workflow fit
Concrete scenarios for the personas Dedoctive actually fits — and what changes day-one when you adopt it.
You need to sign off a decision that a regulator may later challenge. You curate the policy documents, prior decisions and source data into a knowledge model, design a BPMN workflow with a mandatory human review step, and run the case through it.
Outcome: You get a structured output where every claim hyperlinks to the exact source — including the relevant table cell — plus a Response Map showing how the conclusion was assembled, and an explicit gap statement where the evidence does not support an answer.
You are assembling a risk assessment from standards, incident reports, spreadsheets and scanned diagrams. You ingest all formats, then use interactive visuals to explore how information items connect across documents.
Outcome: Hidden connections between apparently unrelated items surface as explorable arguments, and the resulting assessment carries source-level traceability instead of unsupported assertions.
You build a verified knowledge model from regulatory and policy documents, then run specialist multi-step workflows to produce planning outputs and formal diagrams for review.
Outcome: Traceable reports and diagrams that a reviewer can check at source, with the answer restricted to the knowledge most relevant to the question for faster and cheaper runs.
Use Cases
- Audit a compliance decision by tracing every output back to the source document, table cell or image region that supports it.
- Generate defensible risk assessments in supply chain or crisis response scenarios where the reasoning must be reconstructable.
- Build transparent AI workflows for medical evidence review with human sign-off at each governed step.
- Create verified knowledge models from regulatory documents for planning and public-sector policy analysis.
- Produce traceable reports and formal diagrams that a reviewer or regulator can check at source.
- Deploy on-premises or in a private cloud with automated redaction for classified or sensitive data workflows.
Limitations
- Getting value out of Dedoctive is a build project, not a signup: you curate knowledge models, design BPMN workflows and place human-in-the-loop guardrails before outputs are defensible, and the quality of those outputs is bounded by the quality of the sources you curate.
- Because it wraps whichever large language model you attach, and names no specific model, answer fluency depends on that choice rather than on Dedoctive alone.
- The platform is positioned for enterprise deployments, micro-pilots and partner-led projects, so expect an engagement rather than self-service onboarding, and the developer-facing material beyond the Developer Edition IDE was outside what this research pass could verify.
as of 2026-10-08
Verification history
We have re-verified Dedoctive 10 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
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Showing the 6 most recent of 10 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Dedoctive's pricing actually pencils out — and where peers do it cheaper.
Dedoctive sits at the enterprise/regulated end of the market rather than the per-seat productivity end. The free Developer Edition IDE and a free micro-pilot let a technical evaluator prove the provenance and workflow mechanics against one real decision process before any commercial commitment. Compare that with general assistants like ChatGPT or Claude, which cost far less per seat but offer no source-level audit trail, and with specialist document-Q&A tools that cite passages but stop short
Setup time & first value
How long it actually takes to get something useful out of Dedoctive — broken out by persona, not the marketing-page minute.
For a developer or technical evaluator: the free Developer Edition IDE is a download, so you can have a transparent workflow running the same day, and there is an official video tutorial series to follow. For an assurance, compliance or clinical team: expect a project-scale ramp — curating validated sources into a knowledge model, authoring the BPMN workflow and placing human-in-the-loop
Switching to or from Dedoctive
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From general AI chat tools (ChatGPT, Claude): move the decisions that need defensible outputs into curated knowledge models plus governed BPMN workflows, and keep chat tools for low-stakes drafting.
- →From unmanaged document search or shared drives: ingest the same corpus as a validated knowledge model so every answer points at the source item rather than a folder.
- →From manual review spreadsheets: encode the review steps as a BPMN workflow with human-in-the-loop guardrails and let provenance links replace hand-typed citations.
- →From bespoke in-house RAG pilots: reuse the source corpus, but replace ad-hoc retrieval with curated knowledge models and Response Maps for traceability.
- ↗To general assistants (ChatGPT, Claude): viable for low-stakes drafting, but you lose source-level provenance and the explicit 'no answer' behaviour.
- ↗To lighter document-Q&A tools: simpler to run, but they typically stop at passage-level citation rather than table-cell and image-text provenance inside governed workflows.
- ↗To a fully bespoke in-house build: possible where you have the engineering team, but you give up the open-standard workflow tooling and the pre-built domain Navigators.
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Dedoctive”, and we withheld 6: 6 could not be judged, because “Dedoctive” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Dedoctive.
Official links
Tools that pair well with Dedoctive
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Featured Head-to-Head Comparisons
Dedoctive vs Isomorphic Labs
Dedoctive and Isomorphic Labs serve completely different domains and scales. Dedoctive is ideal for organizations needing auditable, evidence-grounded decisions in document-heavy compliance, healthcare, or public sector contexts, with a free IDE and flexible deployment. Isomorphic Labs is a high-stakes drug discovery partner for large pharma, with heavy investment and Nobel Prize-derived AI, but inaccessible to smaller players. Choose Dedoctive if you need defensible transparency; choose Isomorphic Labs only if you are a big pharma with deep pockets and a pipeline for AI-driven therapeutic design.
Dedoctive vs Screenplayiq
ScreenplayIQ and Dedoctive serve completely different purposes: ScreenplayIQ is for screenwriters wanting data-driven script feedback and box office predictions, while Dedoctive is for compliance and risk analysts needing auditable, evidence-based decisions. Your choice should be based on domain—if you write feature films, go with ScreenplayIQ; if you need defensible, traceable outputs from documents, Dedoctive is the clear winner.
Dedoctive vs Praktika
Praktika and Dedoctive address completely different needs. If you want to improve conversational fluency in a language, Praktika's AI tutors with real-time feedback are a strong choice. If you need auditable, evidence-grounded decisions for compliance or safety, Dedoctive's provenance features are unmatched. Choose based on your domain.
Alternatives to Dedoctive
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