We build AI solutions for every challenge,
especially the hardest ones
From genomics and biotech to drug discovery and applied AI — projects with real-world data, complex problems and demanding technical requirements.
Have an AI project? We work with you
Laboratories, companies, universities and researchers: if your project requires deep expertise and dependable results, we can help.
Laboratories
Biotechnology and pharmaceutical companies
Researchers, universities and project owners
From applied AI to advanced genomics
From practical AI tools to complex genomics, biotechnology and drug discovery projects.
Applied Artificial Intelligence15 projects
Intelligent protocol and literature assistant (RAG)
Project overview
An assistant built around your protocols, papers and internal documentation that answers team questions with cited sources.
Outcome
Less time searching for information and traceable answers to recurring questions.
Methods and technologies
Large language models, semantic retrieval, answer verification.
Automated extraction from reports and documents
Project overview
Extract key fields such as names, dates, measurements and outcomes from lab reports, invoices, contracts, forms and scanned PDFs into structured tables or databases.
Outcome
Searchable, standardized records with uncertain entries flagged for human review.
Methods and technologies
OCR, language models, validation rules.
Automated literature review and research gap discovery
Project overview
Collect and cluster publications by topic to identify completed work, overlooked questions and influential papers across your research area.
Outcome
A visual topic map and source-linked summary to support proposals and literature reviews.
Methods and technologies
Text mining, topic clustering, citation-aware summarization.
AI chatbot and intelligent customer support
Project overview
Answer customer questions using your organization’s verified catalog, records and policies, with escalation to a person for complex cases.
Outcome
Reduced support workload and faster responses around the clock.
Methods and technologies
Language models, semantic retrieval, CRM integration.
Inventory and warehouse optimization
Project overview
Forecast demand, optimize stock levels and flag shortages or excess based on historical sales, seasonality and market patterns.
Outcome
Fewer shortages, lower inventory carrying costs and better purchasing plans.
Methods and technologies
Time-series forecasting, optimization, operational dashboards.
Customer management and churn prediction
Project overview
Identify customers at risk of leaving and segment user behavior to guide retention and outreach decisions.
Outcome
More targeted retention strategies and lower customer acquisition costs.
Methods and technologies
Classification, clustering, customer lifetime value modeling.
Insurance pricing and claims forecasting
Project overview
Combine multiple data sources to estimate premiums, detect high-risk groups and forecast outstanding claims, including automotive insurance use cases.
Outcome
More data-driven pricing and reserve planning.
Methods and technologies
ARIMA, neural networks, regression, multisource data integration.
Recommendation systems
Project overview
Recommend products, content or services based on each user’s behavior and preferences.
Outcome
Improved sales opportunities and user engagement.
Methods and technologies
Collaborative filtering, hybrid models, A/B testing.
Expert networks and relationship discovery (E-Connect)
Project overview
Connect people by skills and experience extracted from resumes and publicly available sources to discover relevant experts and contacts.
Outcome
A searchable relationship graph linking related and similar specialists.
Methods and technologies
Language models, web data extraction, graph analysis.
OCR and intelligent document imaging
Project overview
Recognize text in images and scanned documents, including Persian, and extract information suitable for further processing.
Outcome
Searchable and analyzable datasets from scanned images and documents.
Methods and technologies
Computer vision, Persian OCR, image preprocessing.
Computer vision for inspection and recognition
Project overview
Classify, detect and segment objects in images and video for quality inspection, visual recognition and pose estimation.
Outcome
Rapid image-based decision support.
Methods and technologies
Deep neural networks, detection, segmentation and pose estimation.
Image-to-image translation for better training data
Project overview
Convert simulated images into more realistic-looking examples for model training and improved downstream image classification.
Outcome
Cost-effective synthetic training images and potential classification improvements.
Methods and technologies
CycleGAN, GCGAN, diffusion models, vision transformers.
Data warehouse and business intelligence dashboards
Project overview
Consolidate scattered enterprise data into a warehouse and build analytical reports and dashboards for managers.
Outcome
A consistent, current view of business operations.
Methods and technologies
Data warehousing, OLAP, MDX, business intelligence.
Integrating AI models into business workflows
Project overview
Connect AI models with existing applications, databases and operational workflows so prototypes become usable production systems.
Outcome
An end-to-end intelligent workflow with measurable operational outcomes.
Methods and technologies
APIs, data pipelines, deployment and monitoring.
Testing an idea with a minimum viable product (MVP)
Project overview
Validate an AI idea using a focused prototype before committing resources to full development.
Outcome
Evidence on technical feasibility and potential value.
Methods and technologies
Rapid prototyping, success metrics, evaluation.
Biotech, Pharma & Medicine5 projects
Virtual screening and ADMET prediction
Project overview
Rank large compound libraries for a drug target and estimate absorption, toxicity and stability before laboratory testing.
Outcome
A shorter candidate list that can reduce experimental time and cost.
Methods and technologies
Molecular graph learning, docking, molecular-property prediction.
Drug repurposing with knowledge graphs
Project overview
Connect gene, disease, drug and literature evidence in a knowledge graph to identify potential new uses for existing drugs.
Outcome
Repurposing hypotheses supported by interpretable biological evidence.
Methods and technologies
Knowledge graphs, graph neural networks, pathway analysis.
Protein and antibody design and optimization
Project overview
Predict protein structure and stability, interpret mutations and propose candidate improved sequences using protein language models.
Outcome
Candidate sequences for experimental evaluation and structural variant reports.
Methods and technologies
Protein structure prediction, protein language models, free-energy calculations.
Microscopy and digital pathology image analysis
Project overview
Detect and count cells, classify tissues and extract features from slide and microscope images.
Outcome
Deployable computer-vision workflows with accuracy assessed on independent data.
Methods and technologies
Computer vision, transfer learning, vision foundation models.
Medical imaging software (DICOM)
Project overview
Build software for exchanging medical images between scanners and computers and connecting studies to patient workflows.
Outcome
Integrated image-exchange workflows for clinical equipment.
Methods and technologies
DICOM, C#, MySQL, TCP/IP.
Advanced Genomics5 projects
Synthetic patient data with generative models
Project overview
Generate statistically similar tabular and genotype datasets from limited source data for model development with privacy testing.
Outcome
A synthetic-data prototype with distribution comparisons and privacy leakage evaluation.
Methods and technologies
Generative models, distribution validation, membership-inference testing to check whether a record appeared in the original data.
Single-cell and spatial analysis using foundation models
Project overview
Identify cell types and tumor tissue heterogeneity from single-cell and spatial data, including noisy samples.
Outcome
A cellular tissue map and candidate markers for subsequent studies.
Methods and technologies
scRNA-seq, spatial transcriptomics, cell foundation models.
Noncoding variant interpretation with deep learning
Project overview
Predict the regulatory impact of genetic variants outside protein-coding regions when conventional methods are inconclusive.
Outcome
Prioritized regulatory variants for further review when coding variants do not explain findings.
Methods and technologies
DNA sequence deep learning, feature attribution.
Federated learning across laboratories
Project overview
Train a shared model across sites without transferring each laboratory’s raw data outside its own environment.
Outcome
A cross-site model that can leverage multiple datasets while maintaining local data control.
Methods and technologies
Federated learning, secure aggregation, differential privacy.
Multi-omics integration for cancer subtyping
Project overview
Combine genome, expression and methylation data to explore patient subgroups with different prognoses and treatment responses.
Outcome
Candidate clinically meaningful subgroups and an externally evaluated prognostic model.
Methods and technologies
Multi-view factorization, survival analysis, external validation.
Have a different challenge in mind?
Give us 30 minutes. We will listen to your needs and discuss potential approaches, with no obligation to work with us afterward.
Book a free consultationOur process, step by step
At each stage, you know what we do, what we need from you, and what you receive.
Discovery meeting (30 minutes, free)
In a short call, we learn what outcome you need (a paper, product, report, new service, or mentoring) and what data or idea you have. This is not a technical consultation; it helps clarify what we can deliver.
- Your input
- A brief explanation of your goal and available data.
- Deliverable
- A clear overview of feasible work and a recommended collaboration model.
- Timeframe
- 30 minutes
Data review and method design
After signing an NDA, we assess data quality, volume, bias and suitability for your goal, then select an analysis strategy.
- Your input
- Access to appropriately de-identified data and information about data collection.
- Deliverable
- A proposed methods document, including assumptions, risks and success criteria.
- Timeframe
- Several days to one week
Analysis and modeling
We carry out the analysis and provide progress reports at agreed milestones so you can track the project.
- Your input
- Answers to technical questions and feedback on interim findings.
- Deliverable
- Reviewable milestone reports and interim results.
- Timeframe
- Main phase of the project
Interpretation, reporting and delivery
We interpret results for your intended audience, whether executives, laboratory leaders or journal reviewers. We deliver code and documentation to support reproducibility.
- Your input
- Review and approve the final report.
- Deliverable
- Full report, figures, clean code and methods documentation.
- Timeframe
- One to two weeks
Post-delivery support
We remain available after delivery to resolve questions about results and help plan next steps.
- Your input
- Any questions or issues arising after handover.
- Deliverable
- Clarifications, responses and recommendations for next steps.
- Timeframe
- As agreed
From an initial conversation to long-term support
We begin with a free discovery meeting. Specialist services are scoped based on your needs.
Discovery meeting
We ask about your goals, ideas and data, then explain what is feasible and which collaboration approach may suit you.
Technical consultation
Tell us the project requirements. We assess data sufficiency, outline a clear roadmap and help you select an appropriate technical approach.
- Requirements review
- Data sufficiency assessment
- Roadmap and solution selection
End-to-end project delivery
We agree on a proposal, build an MVP and work through your feedback until the final handover.
- Proposal and agreed objectives
- MVP delivery and feedback
- Final results, code and documentation
Ongoing expert mentoring
For teams and researchers who want to do the work themselves with expert support. Regular sessions review progress, resolve technical obstacles and plan the next steps.
- Regular monthly sessions
- Code and analysis reviews
- Technical guidance between meetings
We tackle AI projects, including the most complex
From practical tools to specialist AI
From intelligent assistants and document analysis to genomics, biotech and drug discovery, we bring the expertise a complex project needs.
When challenges become complex
Our strength lies in problems requiring deep biological expertise and complex data, particularly genomics and biotechnology.
Reproducible results and honest assessment
We deliver code and methods so the results can be reproduced. If your data are insufficient, we tell you before the project starts.
Data security and professional standards
Common questions before starting a project.
What is the free 30-minute meeting, and how does it differ from a technical consultation?
The free discovery meeting is obligation-free: we listen to your needs and explain possible approaches. In a technical consultation, we assess requirements and data sufficiency, then propose a roadmap and suitable methods.
Where are my data stored, and who can access them?
Data are stored in controlled systems, and access is limited to authorized project team members with logged access.
Do you sign a non-disclosure agreement before accessing data?
Yes. We do not review project data before an NDA is signed.
Will my data be used to train models for other clients?
No. Each client’s data are used solely for that client’s project.
Who owns the data, code and results?
You retain ownership of your data and results; project code and documentation are delivered according to the agreed scope.
What happens to my data when the project ends?
As agreed, data are returned or securely deleted, with confirmation of deletion.
What if my data are insufficient for the goal?
We tell you during the initial data assessment and suggest feasible alternatives before work begins.
How do you ensure results are reliable and reproducible?
We document methods, version the code and evaluate on independent data where appropriate so results can be reviewed and reproduced.
How do you handle co-authorship and publication?
Publication responsibilities and authorship contributions are agreed in writing before work begins.
Specialist AI consultation
Select a 30-minute AI consultation from 5 PM to 9 PM Iran time. After email verification, payment is required to confirm your slot.
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