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Your AI should get better at your company’s work.

Your AI should get better at your company’s work.

Konovo learns from approved workflows, evaluates AI against the work that matters and helps your team improve without rebuilding everything.

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See how it works

Konovo · Model Lab

Dashboard Screenshot

Konovo · Model Lab

Dashboard Screenshot

AI

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Feature Preview

AI that learns from your work
and improves with every iteration

Turn approved employee workflows into reusable systems. Test models against your own tasks, find what works and deploy verified improvements.

Operational clarity

See project scopes, velocity, and outcomes at a glance.

Release cadence

+18% QoQ

Chart Diagram

On‑time delivery

92%

Operational clarity

See project scopes, velocity, and outcomes at a glance.

Release cadence

+18% QoQ

Chart Diagram

On‑time delivery

92%

Operational clarity

See project scopes, velocity, and outcomes at a glance.

Release cadence

+18% QoQ

Chart Diagram

On‑time delivery

92%

Seamless collaboration

Keep engineers and designers aligned with shared tasks.

PR review: onboarding flow

Merged

Spec update: billing retries

New

Design handoff: settings

Today

Seamless collaboration

Keep engineers and designers aligned with shared tasks.

PR review:
onboarding flow

Merged

Spec update:
billing retries

New

Design handoff:
settings

Today

Build and deploy status

Real time build health and deploy logs tied to releases.

Lead Time

1.9d

Cycle Time

12h

Fail Rate

3%

Error rate spike detected

Investigate

Version downloads

+19%

Build and deploy status

Real time build health and deploy logs tied to releases.

Lead Time

1.9d

Cycle Time

12h

Fail Rate

3%

Error rate spike detected

Investigate

Version downloads

+19%

Rollout controls

Releases, CI targeting and rollbacks to reduce friction.

Impact vs. effort

Auto-calculated

Effort

27%

Impact

High

Release

0.78

Scope QA for v1.4

Due Friday

Promote rollout to 50%

Ready

Rollout controls

Releases, CI targeting and rollbacks to reduce friction.

Impact vs. effort

Auto-calculated

Effort

27%

Impact

High

Release

0.78

Scope QA for v1.4

Due Friday

Promote rollout to 50%

Ready

Private by design

Contact us

Process

Learn > Evaluate > Improve > Deploy

A continuous learning loop built around the workflows your team already performs.

Learn

Capture approved work, decisions and corrections from real employee workflows.

Konovo identifies recurring tasks and turns approved demonstrations into structured workflow specifications, reusable examples and business-specific rules. The result is a clear record of how good work gets done.

  1. Approved workflow capture

  2. Business rules and exceptions

  3. Verified examples of completed work

  4. Employee corrections and feedback

Workflow library

Draft

Chart Diagram

Invoice processing

Approved

Learn

Capture approved work, decisions and corrections from real employee workflows.

Konovo identifies recurring tasks and turns approved demonstrations into structured workflow specifications, reusable examples and business-specific rules. The result is a clear record of how good work gets done.

  1. Approved workflow capture

  2. Business rules and exceptions

  3. Verified examples of completed work

  4. Employee corrections and feedback

Workflow library

Draft

Chart Diagram

Invoice processing

Approved

Evaluation run · 01

Candidate models

Test cases

48 cases

Task quality

Measured

Inference cost

Per task

Extract invoice fields

Baseline

Check duplicate invoice

Candidate

Validate totals

Queued

Evaluation progress

Evaluate

Test candidate models against the same business tasks.

Konovo builds evaluations from verified examples and compares candidate models and workflow versions. Measure task quality, latency and cost against the work your company actually performs.

  1. Company-specific evaluation datasets

  2. Compare models and prompts

  3. Measure cost and latency

  4. Catch regressions before deployment

Improve

Make the change only when the evidence supports it.

A better implementation might be a stronger workflow, a different model, a prompt change or a specialized adapter. Test it in an isolated environment, review the results and deploy with a rollback path.

  1. Workflow and prompt improvements

  2. Model selection and routing

  3. Fine-tuning when justified

  4. Approval and rollback

Candidate update

Under review

Evaluation results

Task success

Chart Diagram

Release gate

Pending approval

Previous version

v1

Improve

Make the change only when the evidence supports it.

A better implementation might be a stronger workflow, a different model, a prompt change or a specialized adapter. Test it in an isolated environment, review the results and deploy with a rollback path.

  1. Workflow and prompt improvements

  2. Model selection and routing

  3. Fine-tuning when justified

  4. Approval and rollback

Candidate update

Under review

Evaluation results

Task success

Chart Diagram

Release gate

Pending approval

Previous version

v1

Testimonials

Built around how your company works

Konovo turns approved employee workflows into private benchmarks and business-specific AI capabilities.

01

Workflow learning

Approved employee work

Turn recurring tasks, decisions and corrections into reusable workflow specifications.

02

Private evaluation

Company-specific benchmarks

Test candidate models against the same cases your business actually cares about.

03

Continuous improvement

Verified changes

Improve workflows, models and prompts based on evidence, with approval and rollback.

Pricing

Choose where your AI runs

Run locally, inside your own infrastructure or on managed GPU capacity.

01

On-device execution

LOCAL

Local runtime

For compatible models and everyday tasks

Local

compute

Discuss deployment

Deployment includes:

  1. Local model runtime

  2. User-controlled capture

  3. Encrypted local storage

  4. On-device inference

  5. Background evaluations

  6. Device resource limits

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02

Customer-controlled

PRIVATE

Private infrastructure

For customer-owned cloud or on-premises environments

Your

infrastructure

Discuss deployment

Deployment includes:

  1. Dedicated customer environment

  2. Private model endpoints

  3. Customer data boundaries

  4. Policy-controlled evaluation

  5. Versioned model artifacts

  6. Audit and approval controls

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03

Managed GPU capacity

MANAGED

Managed compute

For heavier inference, evaluation and training jobs

On

demand

Discuss deployment

Deployment includes:

  1. Managed model inference

  2. Queued evaluation jobs

  3. Fine-tuning when justified

  4. GPU resource management

  5. Versioned model artifacts

  6. Usage and job monitoring

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Deployment options are scoped around your security, infrastructure and governance requirements.

Talk to sales

FAQ

Questions about Konovo

How the platform learns from approved work, evaluates models and helps teams improve AI workflows.

  1. What does Konovo do?

  2. Does Konovo record everything employees do?

  3. Does our data have to leave our environment?

  4. How does Konovo compare AI models?

  1. Does Konovo fine-tune a model automatically?

  2. What happens when a model changes or is retired?

  3. Can we use our own GPUs?

  4. How do we join the private beta?

  1. What does Konovo do?

  2. Does Konovo record everything employees do?

  3. Does our data have to leave our environment?

  4. How does Konovo compare AI models?

  1. Does Konovo fine-tune a model automatically?

  2. What happens when a model changes or is retired?

  3. Can we use our own GPUs?

  4. How do we join the private beta?

Have a workflow in mind? Talk to our team.

Talk to us

Give your business AI that gets better at its work.

Start with one workflow. Build a private benchmark. Improve the AI your teams rely on.

Request a demo

Request a demo

AI

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