Business problem in. Production AI out.
Faster, cheaper and more reliable than the tools you're comparing.
We turn your problem into an architecture: agents, retrieval, voice, data pipelines and the models behind them, chosen on evidence, engineered for latency and cost, and handed over with the tests that prove it works.
- Architecture chosen on evidence, not vendor pitch
- Latency and cost engineered from sprint one
- Evals, guardrails and traces in every system
- Channels
- Agents & orchestration
- Retrieval & memory
- Models & routing
- Data platform
- Evals · guardrails · observability
What we do, without the jargon.
Whether you run one shop or a global team, the shape is the same: you bring a problem and the data you have, we build the system on top of what already exists, and you end up owning something that runs and scales.
You bring the problem and whatever data you have
Spreadsheets, an old ERP, WhatsApp chats, paper forms. All fine.We build on top of what already exists
No rip-and-replace. We connect the old systems and add the new layer.It runs, it scales, and you own it
Your cloud accounts, your code, documentation for whoever comes next.Six people who come to us
Real shapes of work, from a single store to research-level systems. If yours is not here, it is probably a mix of two.
One store to every doorstep
Orders on WhatsApp and a simple app, live inventory, delivery partners plugged in, and the same setup copied city by city. The way quick-commerce apps like Blinkit work, sized for you.
What we build
- Storefront and WhatsApp ordering
- Inventory and billing kept in sync
- Delivery-partner and payment APIs
- Copy the setup to the next city
Mobile-first, a human always reachable
Technicians, agents, drivers: the work happens outside the office and the signal is not always there. The app works offline, AI drafts the paperwork, and a person is one tap away, because a phone number is a requirement, not a feature.
What we build
- Offline-first mobile app
- AI drafts reports and forms
- Escalation to a human by call or WhatsApp
- Dispatch, tracking and proof of work
Build on top of what you already have
The ERP is old, the CRM is older, and the reports live in Excel. We do not ask you to replace them. We connect them, clean the data, and put the new layer on top: search, automation, assistants.
What we build
- Integration layer over legacy systems
- Data cleaned, governed and trusted
- AI on top: search, assistants, automation
- Scales to new teams and regions
From a normal website to deep integrations
Start with a fast site and payments. Then CRM, support and analytics. Then agents that answer, sell and follow up. One team, one architecture that grows with you.
What we build
- Website, payments and CRM
- Support desk and analytics
- Automations, then agents
- Ready for languages, regions, compliance
Idea to product, explained in plain words
We explain every decision in language you can repeat to an investor, and we document everything, so you can hire your own engineers later without starting over.
What we build
- Scope and plan in plain language
- Working product in weeks
- Full documentation and handover
- Your accounts, your code
Research-level work when you need it
Fine-tuning, evaluation frameworks, retrieval engines, interpretability, custom architectures. We work at the level of the papers and hand over the experiments too.
What we build
- Fine-tuning and evaluation suites
- Retrieval and agent architectures
- Interpretability and audits
- Reproducible experiments and reports
- B2B
- B2C
- D2C shops
- Field services
- Enterprises
- Founders
- Research teams
- Non-technical owners
Built on the platforms your team already trusts
Problems we solve, and the architecture behind each
Every engagement starts from a business problem, not a technology. Here is how the common ones map to a system design and to outcomes the industry has documented.
Support queues that never shrink
Tier-1 questions consume most of the team's day, answers vary by agent, and customers wait. Generic chatbots deflect badly because they do not know your policies or your systems.
How the system works
- Customer message
- Intent & policy check
- Retrieve from your docs & orders
- Answer or act via tools
- Escalate with context
Outcome: Klarna's assistant handled two thirds of customer chats in its first month and cut resolution time from 11 minutes to under two; Intercom reports Fin resolving 76% of conversations on average. Klarna press release
ArchitectureCalls missed, callers on hold
Clinics, dealerships and service businesses lose bookings after hours and during peaks. IVR menus frustrate callers and staff repeat the same ten conversations all day.
How the system works
- Call arrives
- Streaming speech-to-text
- Agent reasons & checks calendar / CRM
- Streaming text-to-speech
- Book, confirm, hand off
Outcome: Voice agents replacing IVR resolve a majority of qualified calls automatically (66% at one Parloa customer) and cut wait times by a third or more, at turn latencies under a second. Parloa customer results
ArchitectureDocuments keyed in by hand
Invoices, KYC files, claims and contracts arrive as PDFs and photos. People retype them, errors slip through, and the backlog grows every month-end.
How the system works
- Ingest PDF / image / email
- Classify document type
- Extract to a schema
- Validate & score confidence
- Auto-post or route to review
Outcome: Documented deployments classify documents in under a second, turn day-long claims backlogs into minutes, and reach 85% no-touch invoice processing within six months with a seven-month payback. DXC with Claude; Vic.ai
ArchitectureAnswers buried in ten systems
Policies live in SharePoint, decisions in email, procedures in Confluence and history in tickets. New staff take months to become useful and experts answer the same questions daily.
How the system works
- Connect sources
- Chunk with context, embed + index
- Hybrid retrieval + rerank
- Cited answer with permissions
- Feedback into evals
Outcome: Contextual chunking with hybrid search and reranking cuts retrieval failures by 67% versus plain vector search, which is the difference between an assistant people trust and one they abandon. Anthropic: Contextual Retrieval
ArchitectureSales conversations stuck on personal phones
Orders, questions and promotions run through WhatsApp with no history, no automation and no way to see what drove revenue.
How the system works
- Ad or QR opens chat
- AI agent answers from catalogue
- Cart & payment in chat
- Order synced to store
- Campaign & follow-up
Outcome: 53% of retailers already automate messaging on the WhatsApp Business Platform (Infobip), and the same grounded-agent pattern turns that channel into a store, a support desk and a campaign tool with attribution. Infobip WhatsApp statistics
ArchitectureEvery question needs an analyst
Leaders wait days for a report, dashboards disagree with each other, and the data team is a queue. Raw data sits in the warehouse without becoming a decision.
How the system works
- Raw sources
- Lakehouse with partitions & quality checks
- Semantic layer of metrics
- Text-to-SQL agent
- Dashboards & alerts
Outcome: In dbt's own test, questions answered through a governed semantic layer reached 83% accuracy, against a 16.7% raw-SQL baseline in the data.world benchmark it replicated; vendors report time-to-insight falling by over 99% with 62% adoption within a year. dbt: the semantic layer as the data interface for LLMs
ArchitectureHow an engagement actually runs, in detail
No mystery phases. Here is what happens at each stage, what we need from you, and what you walk away with.
Step 01 · 60 min · free
Discovery call
A working session with a senior engineer, not a sales rep. Before the call we research your company, industry, tech stack and recent initiatives. On the call we map the problem, the workflow around it and the constraints, and we tell you honestly whether AI is the right tool before anyone spends money.
What happens
- Opening (10 min): one question anchors everything: which area of the business costs you the most time, effort or money, and what metric would prove it improved?
- Process mapping (30 min): we walk the workflow end to end: who does what, in which systems, at what volume, with what turnaround and exception rate.
- Opportunity surfacing (20 min): we map the data (where it lives, who owns it, how clean and fresh it is, whether it contains personal or regulated data) and sketch two or three candidate approaches with rough effort.
- Constraints and next steps (10 min): cloud and data-residency rules, security review, compliance, budget band, deadline, and whether the next step is a deep-dive sprint, a scoped pilot or an honest “not yet”.
What we ask of you
- The workflow as it runs today, including the messy exceptions
- Monthly volumes, current cost or time per item, and service-level targets
- Systems involved (CRM, ERP, helpdesk, warehouse, phone, WhatsApp) and who administers them
- Who decides, who will own the system after launch, and the timeline you are working to
- Anything you have already tried, and why it stalled
What you get
- A written summary within 48 hours
- A feasibility view: green, amber or red, with the reasons
- A suggested pilot scope and an indicative budget band
- A short intake list of what we would need to see next
Reference architectures we design from
Pick a pattern and watch a request move through it, top to bottom. Hover any part to see what it does.
Single agent with tools
One model, a toolbox, and a loop that decides what to call next.
across every level
Hover or tap any part to see what it does. The light shows the order a request moves through.
The ecosystem we build with, layer by layer
Vendor-neutral and opinionated: every layer has a short list of tools we trust in production, and we will tell you which one fits and why.
Models, sorted by the job they do
We benchmark frontier and open-weight models on your data and route each task to the cheapest one that meets the bar. The frontier moves every few weeks, so the routing layer is built to swap models without touching your product.
A narrow step: the smallest model that passes the eval wins.
Frontier
The hardest reasoning and long agent runs
Workhorse
Most production agent and chat steps
Fast & cheap
Classify, extract, route and summarise at volume
Open-weight
Self-host for privacy, cost or fine-tuning
Hover or tap a model to see what it is for. We route every request to the cheapest crate that passes your evals.
And every other layer of the stack
Agent frameworks & protocols
From raw data to something a model, and a person, can trust
Models are only as good as the tables and documents behind them. We design the ingestion, storage and quality layer first: partitioned lakehouse tables, streaming where freshness matters, tests on every transformation, and one governed definition of each metric, so what reaches a model or a dashboard can be trusted.
Raw data → insight
watch the bad records drop out at silverDocuments → searchable knowledge
- 1DocumentsPDF, wiki, tickets, email
- 2Parselayout, tables, OCR
- 3Chunkby structure, with context
- 4Enrichmetadata, permissions
- 5Indexvectors + keywords
- 6Retrievehybrid, reranked, cited
- 7Evaluategolden questions, feedback
Practices built into every pipeline
Partitioning & clustering
Why our systems are faster and cheaper than the tools you are comparing
Speed and cost are architecture decisions, not vendor promises. Tap a lever to see how it works and the effect size the platforms publish.
Prompt caching
90% off cached input
The landscape we design for, with sources.
TrendingThe daily dose, 11 Sep 202612 items · 29 claims checked · 6 corrected
Read the doseWe read everything so you can trust what we build
Model releases, research papers, what the industry actually uses. Dated, sourced, checked line by line.
Seven capabilities. One accountable team.
From strategy to the data platform underneath, we cover every layer of an AI product so nothing falls between vendors.
Reliability by design. Not by hope.
Demos are easy. We build the parts that make AI dependable when real users, real data and real money are involved.
Audit-ready from day one
- SOC 2 ready
- ISO 27001 aligned
- GDPR
- HIPAA-aware
- NDA on day one
Azure, AWS, GCP or your own servers, in your accounts. We pick the best cost and integrations for your workload and document everything end to end, so if you hire your own engineers later or stop working with us, nothing breaks and nothing is hidden.
Azure, AWS, GCP or your own servers, in your accounts. We pick the best cost and integrations for your workload and document everything end to end, so if you hire your own engineers later or stop working with us, nothing breaks and nothing is hidden.
Build the whole product on Azure, AWS, GCP or whatever you already run. No lock-in.
Any tech stack you choose, we help you get the most out of it: the best cost for your traffic, the integrations you already pay for, and a system your own engineers can take over on day one if you ever want them to.
- Microsoft Azure
- Amazon Web Services
- Google Cloud
- Databricks
- Vercel
- Your own servers
Best cost for your workload
We compare the clouds and the models for your actual traffic, then commit to the cheapest setup that meets the bar. Reserved capacity, caching, routing and batch where they pay off.
The integrations you already use
Payments, CRM, ERP, WhatsApp, email, analytics. We connect to what you have rather than replacing it.
Leave whenever you want. Nothing breaks.
The stack is standard and named up front. If you hire your own engineers or stop working with us, they inherit a documented system, not a mystery.
The handover pack
end to end, with time and proof- Architecture decision records: why each choice was made
- End-to-end documentation of every flow, with timings
- Runbooks, alerts and on-call notes
- Evaluation reports with the numbers behind them
- Traces and cost dashboards, live in your accounts
- Infrastructure as code, deployed into your cloud
- Recorded walkthroughs for the next team
- A dated handover plan, signed off with proof
Everything is delivered into your accounts as we go, not at the end. When the project closes you already have the keys, the docs and the history of every decision with its date.
Get the clarity you deserve
Straight answers to the questions we hear most. Ask us anything else on a call.
Nothing breaks. The stack is standard and agreed up front, everything is deployed into your own cloud accounts as we go, and you receive a handover pack: architecture decision records, end-to-end documentation with timings, runbooks, evaluation reports, traces and cost dashboards, infrastructure as code and recorded walkthroughs. Your team, or the next vendor, inherits a documented system.
Nothing breaks. The stack is standard and agreed up front, everything is deployed into your own cloud accounts as we go, and you receive a handover pack: architecture decision records, end-to-end documentation with timings, runbooks, evaluation reports, traces and cost dashboards, infrastructure as code and recorded walkthroughs. Your team, or the next vendor, inherits a documented system.
Let's build intelligent systems that drive growth
Tachyon is the engineering partner for teams that need AI in production, not in a deck. Start with a free 60-minute discovery call.
Talk to experts about your product idea
Every great partnership begins with a conversation. Whether you are exploring possibilities or ready to scale, tell us what you are actually trying to build.
- ubheshubham.37@gmail.com
- +91 84592 96471
- Clients worldwide · English
- Pune, India · Headquarters