From the first call to a system your team runs, with nothing hidden
Six stages, each with a clear purpose, a clear ask of you and a clear deliverable. This is the same process whether the outcome is a voice agent, a knowledge assistant or a data platform.
The path at a glance
- 1Discovery call60 min · free
- 2Deep-dive & data audit1–2 weeks
- 3Architecture & stack selection1 week
- 4Pilot build4–8 weeks
- 5Production hardening & rollout2–6 weeks
- 6Operate & improveongoing
Each stage in detail
Select a stage to see what happens, what we ask of you and what you receive.
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
The decision matrix behind every architecture recommendation
Six questions decide most of the design. We answer them with your data during the deep-dive, and we write down why the alternatives lost.
| Question | If yes | If no |
|---|---|---|
| Are the steps known in advance? | LLM workflow | Agent with tools |
| Must answers cite your documents? | Hybrid RAG with reranking | Direct model call with structured output |
| Does the task span many systems or skills? | Supervisor multi-agent with checkpoints | Single agent |
| Is the interface a phone call? | Voice agent, cascaded or speech-to-speech | Chat, WhatsApp or in-app copilot |
| Is the task narrow, high-volume and plateaued on prompting? | Fine-tune a small model | Prompt a frontier model with routing |
| Does it need an answer in seconds? | Real-time path with caching and streaming | Batch pipeline at half the price |
The targets every system is designed and monitored against
Choose the model that fits your vision
Fixed scope when the outcome is clear, a dedicated team when the roadmap is alive, or senior engineers inside your own squad.
Fixed-scope pilot
A defined outcome, timeline and price after the deep-dive sprint. Best for a first system.
- Scoped from the audit and architecture doc
- Weekly demos and releases
- Fixed price with change control
Dedicated AI team
A cross-functional squad embedded with your product team for a quarter or longer.
- AI, data, product and design in one team
- Monthly retainer, flexible roadmap
- Knowledge transfer built in
Staff augmentation
Senior AI or data engineers who join your team and your rituals from week one.
- Time-zone aligned
- Start within two weeks
- Scale up or down monthly
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.
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
What we engineer in for speed and cost
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
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.
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